CN110707684B - Control method and system of adaptive wide-area damping controller based on immune mechanism - Google Patents
Control method and system of adaptive wide-area damping controller based on immune mechanism Download PDFInfo
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Abstract
The invention discloses a control method and a system of an adaptive wide area damping controller based on an immune mechanism, comprising the following steps: carrying out linearization processing on the power grid system model in a typical operation mode, and determining an optimal control place and a feedback signal so as to determine a control loop; setting parameters of a manual immune wide area control fixed link; applying the set parameters to the artificial immunity fixed control link, and setting the restraint range of the stimulation factor and the inhibition factor in the artificial immunity wide-area adaptive control link; and determining an objective function according to a preset fault set, establishing an artificial immunity wide-area adaptive control link optimization model, and performing iterative training to determine optimal values of the stimulation factors and the inhibition factors. The invention adjusts the parameters of the original controller on line according to the response output by the system, the control principle is simple and effective, and the invention has self-adaptability; the method has a remarkable effect of inhibiting low-frequency oscillation in a power system interval, and enhances the dynamic stability of the system under unknown faults and disturbances.
Description
Technical Field
The invention relates to the technical field of power system control, in particular to a control method and a control system of an adaptive wide-area damping controller based on an immune mechanism.
Background
Along with the gradual formation of the interconnection area of the power grid in China, the complex network structure of the power system can cause the low-frequency oscillation of the power grid at any time. The existing generator excitation control mainly based on local compensation is difficult to meet the damping requirement of power grid operation. The wide-area measurement system can provide synchronous measurement data of important units and nodes in the interconnected power grid, and overcomes the defects that local feedback signals are poor in observability and the integral characteristics of the power grid are limited. The low-frequency oscillation is taken as an important factor influencing the safe and stable operation of a power grid, and the wide-area damping control design is always taken as a hot spot problem explored by a student.
In the research of wide-area damping control design, a large number of theoretical methods are applied. The traditional controller design carries out linearization processing near a stable working point and determines related parameters as constants, if the running conditions change, the generators near the fault point lose the original cluster coherence, and the setting process usually ignores the interactive response among the units, thereby greatly reducing the control performance and even possibly deteriorating the control effect. Therefore, in order to achieve the damping control effect of the complex power grid under each operation mode, a control method of a self-adaptive wide-area damping controller needs to be designed.
Disclosure of Invention
The invention provides a control method and a control system of a self-adaptive wide-area damping controller based on an immune mechanism, which aim to solve the problem of how to control the wide-area damping controller so as to inhibit low-frequency oscillation between system intervals.
In order to solve the above problems, according to an aspect of the present invention, there is provided a control method of an adaptive wide area damping controller based on an immune mechanism, the wide area damping controller including an artificial immune wide area control fixed link and an artificial immune wide area adaptive control link; the method comprises the following steps:
carrying out linearization processing on a power grid system model in a typical operation mode, calculating a comprehensive geometric controllable observability index according to an input signal and an output signal of a wide-area damping controller, and determining an optimal control place and a feedback signal according to the comprehensive geometric controllable observability index so as to determine a control loop;
according to the control loop, setting parameters of an artificial immune wide area control fixed link by a phase compensation method; wherein the parameters include: gain factor and a dc blocking time constant;
applying the set parameters to the artificial immunity fixed control link, and setting the restraint range of the stimulation factor and the inhibition factor in the artificial immunity wide-area adaptive control link;
determining an objective function according to a preset fault set, establishing an artificial immunity wide area adaptive control link optimization model according to the objective function and the constraint ranges of the stimulation factor and the inhibition factor, and performing iterative training on the artificial immunity wide area adaptive control link optimization model to determine the optimal values of the stimulation factor and the inhibition factor.
Preferably, the linearizing the power grid system model in the typical operation mode includes:
wherein, x (t), y (t), u (t) are the state, output and control vector of the power grid system in sequence, A is an n multiplied by n order state matrix; b is an n multiplied by p order input matrix; c is a q multiplied by n order output matrix, and the characteristic value calculated by the matrix A on the complex plane represents the small interference stability degree of the power grid system.
Preferably, the calculating a comprehensive geometry controllable observability index according to the input signal and the output signal of the wide-area damping controller comprises:
Gcoi(i,j)＝goj(k)gck(k)，
wherein G iscoi(i, j) is a comprehensive geometric controllable observability index; goj(i) The observability index of the power grid system in the oscillation mode k is obtained; gck(i) The controllability index of the power grid system in the oscillation mode k is obtained; c. CjIs the jth row of the output matrix C; biIs the ith column of the input matrix B;
is cjAnd
the geometric angle of (A); theta (psi)i,bk) Is b iskAnd psikThe geometric angle of (c).
Preferably, the adjusting the parameters of the artificial immune wide area control fixed link by the phase compensation method includes:
wherein G iswpssA transfer function of an artificial immunity wide area control fixed link; k is the gain coefficient of the gain link; t isWIs a high pass filter coefficient; tm is the stopping time constant, m is 1,2,3,4, and T3＝T1，T4＝T2；fkThe oscillation frequency of the interval oscillation mode k corresponding to the preset frequency range is the oscillation frequency; wherein, the gain coefficient and the blocking time constant are determined according to the operation requirement of the power grid system and the specific damping control effect.
Preferably, the establishing of the artificial immunity wide-area adaptive control link optimization model comprises:
pi(t)＝pi-standard+Δpi(t)，
wherein, pi-standardGain K calculated for phase compensation of the system through the control loop obtained before and lead-lag element Ti(i＝1,2,3,4)，Δpi(T) is the variation of the fixed link parameters at time T, namely, delta K (T), delta T1(t),ΔT2(t),ΔT3(t),ΔT4(t)；pi(t) is the controller parameters updated by the immune adaptive link; Δ ωij(t) is the relative angular velocity between different units, i.e. the input signal for control; j is determined from a predetermined set of faultsAn objective function; p is the fault category of the faults in the preset fault set; n is the number of the generator sets; delta omega (t) is the time-domain rotor angular speed deviation at the time t of the nth unit; alpha is alphapDetermining the weight coefficient according to the specific operation condition of the power grid system; m isminIs a stimulating factor m1iAnd the inhibitor m2iThe minimum value of the constraint range of (d); m ismaxIs a stimulating factor m1iAnd the inhibitor m2iIs the maximum value of the constraint range of (2).
Preferably, the iteratively training the artificial immune wide-area adaptive control element optimization model to determine the optimal values of the stimulation factor and the inhibition factor comprises:
randomly selecting values in a constraint range to assign values to each stimulating factor and each inhibiting factor in the artificial immune wide-area adaptive control link;
judging whether the objective function values corresponding to the current stimulation factors and the current inhibition factors are smaller than or equal to a preset objective function threshold, if so, determining the values of the current stimulation factors and the current inhibition factors as optimal values; otherwise, judging whether the current iteration number reaches a preset iteration number threshold value; if the current iteration times are equal to the preset iteration time threshold, selecting the values of the stimulation factor and the inhibition factor corresponding to the minimum objective function value as optimal values; if the current iteration times are smaller than the preset iteration time threshold, adjusting the values of each stimulation factor and each inhibition factor in the artificial immune wide-area adaptive control link according to a preset control strategy, and whether the objective function values corresponding to the current stimulation factors and the inhibition factors are smaller than or equal to the preset objective function threshold or not.
According to another aspect of the invention, a control system of an adaptive wide-area damping controller based on an immune mechanism is provided, wherein the wide-area damping controller comprises an artificial immune wide-area control fixed link and an artificial immune wide-area adaptive control link; the system comprises:
the control loop determining unit is used for carrying out linearization processing on a power grid system model in a typical operation mode, calculating a comprehensive geometric controllable observability index according to an input signal and an output signal of the wide-area damping controller, and determining an optimal control place and a feedback signal according to the comprehensive geometric controllable observability index so as to determine a control loop;
the parameter setting unit is used for setting parameters of the artificial immune wide area control fixed link through a phase compensation method according to the control loop; wherein the parameters include: gain factor and a dc blocking time constant;
the setting unit is used for applying the set parameters to the artificial immunity fixed control link and setting the constraint ranges of the stimulation factors and the inhibition factors in the artificial immunity wide-area adaptive control link;
and the optimal value determining unit is used for determining an objective function according to a preset fault set, establishing an artificial immunity wide area adaptive control link optimization model according to the objective function and the constraint ranges of the stimulation factor and the inhibition factor, and performing iterative training on the artificial immunity wide area adaptive control link optimization model to determine the optimal values of the stimulation factor and the inhibition factor.
Preferably, the control loop determining unit is configured to perform linearization on a power grid system model in a typical operation mode, and includes:
wherein, x (t), y (t), u (t) are the state, output and control vector of the power grid system in sequence, A is an n multiplied by n order state matrix; b is an n multiplied by p order input matrix; c is a q multiplied by n order output matrix, and the characteristic value calculated by the matrix A on the complex plane represents the small interference stability degree of the power grid system.
Preferably, the control loop determining unit calculates a comprehensive geometrically controllable observability index according to the input signal and the output signal of the wide-area damping controller, and includes:
Gcoi(i,j)＝goj(k)gck(k)，
wherein G iscoi(i, j) is a comprehensive geometric controllable observability index; goj(i) The observability index of the power grid system in the oscillation mode k is obtained; gck(i) The controllability index of the power grid system in the oscillation mode k is obtained; c. CjIs the jth row of the output matrix C; biIs the ith column of the input matrix B;
is cjAnd
the geometric angle of (A); theta (psi)i,bk) Is b iskAnd psikThe geometric angle of (c).
Preferably, the parameter tuning unit tunes the parameter of the artificial immune wide area control fixed link by a phase compensation method, and includes:
wherein G iswpssA transfer function of an artificial immunity wide area control fixed link; k is the gain coefficient of the gain link; t isWIs a high pass filter coefficient; tm is the stopping time constant, m is 1,2,3,4, and T3＝T1，T4＝T2；fkThe oscillation frequency of the interval oscillation mode k corresponding to the preset frequency range is the oscillation frequency; wherein the increase is determined according to the operation requirement of the power grid system and the specific damping control effectGain factor and a dc blocking time constant.
Preferably, the establishing of the artificial immunity wide-area adaptive control link optimization model comprises:
pi(t)＝pi-standard+Δpi(t)，
wherein p isi-standardGain K calculated for phase compensation of the system through the control loop obtained before and lead-lag element Ti(i＝1,2,3,4)，Δpi(T) is the variation of the fixed link parameters at time T, namely, delta K (T), delta T1(t),ΔT2(t),ΔT3(t),ΔT4(t)；pi(t) is the controller parameters updated by the immune adaptive link; Δ ωij(t) is the relative angular velocity between different units, i.e. the input signal for control; j is a target function determined according to a preset fault set; p is the fault category of the faults in the preset fault set; n is the number of the generator sets; delta omega (t) is the time-domain rotor angular speed deviation at the time t of the nth unit; alpha is alphapDetermining the weight coefficient according to the specific operation condition of the power grid system; m isminIs a stimulating factor m1iAnd the inhibitor m2iThe minimum value of the constraint range of (d); m ismaxIs a stimulating factor m1iAnd the inhibitor m2iIs the maximum value of the constraint range of (2).
Preferably, the optimal value determining unit, which iteratively trains the artificial immune wide-area adaptive control element optimization model to determine the optimal values of the stimulation factor and the inhibition factor, includes:
randomly selecting values in a constraint range to assign values to each stimulating factor and each inhibiting factor in the artificial immune wide-area adaptive control link;
judging whether the objective function values corresponding to the current stimulation factors and the current inhibition factors are smaller than or equal to a preset objective function threshold, if so, determining the values of the current stimulation factors and the current inhibition factors as optimal values; otherwise, judging whether the current iteration number reaches a preset iteration number threshold value; if the current iteration times are equal to the preset iteration time threshold, selecting the values of the stimulation factor and the inhibition factor corresponding to the minimum objective function value as optimal values; if the current iteration times are smaller than the preset iteration time threshold, adjusting the values of each stimulation factor and each inhibition factor in the artificial immune wide-area adaptive control link according to a preset control strategy, and whether the objective function values corresponding to the current stimulation factors and the inhibition factors are smaller than or equal to the preset objective function threshold or not.
The invention provides a control method and a system of an adaptive wide area damping controller based on an immune mechanism, comprising the following steps: carrying out linearization processing on the power grid system model in a typical operation mode, and determining an optimal control place and a feedback signal so as to determine a control loop; according to the control loop, setting parameters of an artificial immune wide area control fixed link by a phase compensation method; applying the set parameters to the artificial immunity fixed control link, and setting the restraint range of the stimulation factor and the inhibition factor in the artificial immunity wide-area adaptive control link; and determining an objective function according to a preset fault set, establishing an artificial immunity wide-area adaptive control link optimization model, and performing iterative training to determine optimal values of the stimulation factors and the inhibition factors. The invention adjusts the parameters of the original controller on line according to the response output by the system by using the immunity mechanism, the control principle is simple and effective, and the invention has self-adaptability; an objective function considering a fault set consisting of typical fault modes is established, so that the robustness is improved; and an intelligent algorithm is used for carrying out multi-target optimization on the immune control parameters, so that the discrete and complex nonlinear problem is well solved; the method has the advantages of obviously inhibiting the low-frequency oscillation in the power system interval, enhancing the dynamic stability of the system under unknown faults and disturbance, along with simple method and providing a solution for inhibiting the low-frequency oscillation in the system interval.
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A more complete understanding of exemplary embodiments of the present invention may be had by reference to the following drawings in which:
FIG. 1 is a flow chart of a control method 100 for an adaptive wide-area damping controller based on an immunization scheme according to an embodiment of the present invention;
FIG. 2 is a block diagram of an architecture of an immune adaptive wide area damping controller according to an embodiment of the present invention;
FIG. 3 is a model of an exemplary four-machine two-zone system, which may be used in accordance with an embodiment of the present invention;
FIG. 4 is a graph showing the response of G1 and G3 to the angular velocity of the unit in case of a test system failure 1 according to the embodiment of the present invention;
FIG. 5 is a graph illustrating the dynamic variation of control parameters during a fault 1 in a test system according to an embodiment of the present invention;
FIG. 6 is a graph of response of G1 and G3 to the angular velocity of the unit at fault 2 for the test system according to the embodiment of the invention;
FIG. 7 is a graph illustrating the dynamic variation of control parameters during fault 2 of a test system according to an embodiment of the present invention;
FIG. 8 is a graph of the response of G1 and G3 to the angular velocity of the unit at fault 3 of the test system according to the embodiment of the invention;
FIG. 9 is a graph illustrating the dynamic variation of control parameters during fault 3 of a test system according to an embodiment of the present invention;
FIG. 10 is a graph of the response of G1 and G3 to the angular velocity of the unit at fault 4 of the test system according to the embodiment of the invention;
fig. 11 is a schematic structural diagram of a control system 1100 of an adaptive wide-area damping controller based on an immunization scheme according to an embodiment of the invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
Fig. 1 is a flow chart of a control method 100 of an adaptive wide-area damping controller based on an immunization scheme according to an embodiment of the present invention. As shown in fig. 1, the control method of the adaptive wide-area damping controller based on the immune mechanism provided by the embodiment of the invention uses the immune mechanism for reference, and adjusts the parameters of the original controller on line according to the response of the system output, so that the control principle is simple and effective, and has adaptivity; an objective function considering a fault set consisting of typical fault modes is established, so that the robustness is improved; and an intelligent algorithm is used for carrying out multi-target optimization on the immune control parameters, so that the discrete and complex nonlinear problem is well solved; the method has the advantages of obviously inhibiting the low-frequency oscillation in the power system interval, enhancing the dynamic stability of the system under unknown faults and disturbance, along with simple method and providing a solution for inhibiting the low-frequency oscillation in the system interval. The wide-area damping controller in the control method 100 of the adaptive wide-area damping controller based on the immune mechanism provided by the embodiment of the invention comprises an artificial immune wide-area control fixing link and an artificial immune wide-area adaptive control link, the method 100 starts from step 101, in step 101, a power grid system model in a typical operation mode is subjected to linearization processing, a comprehensive geometric controllable observability index is calculated according to an input signal and an output signal of the wide-area damping controller, and an optimal control place and a feedback signal are determined according to the comprehensive geometric controllable observability index so as to determine a control loop.
Preferably, the linearizing the power grid system model in the typical operation mode includes:
wherein, x (t), y (t), u (t) are the state, output and control vector of the power grid system in sequence, A is an n multiplied by n order state matrix; b is an n multiplied by p order input matrix; c is a q multiplied by n order output matrix, and the characteristic value calculated by the matrix A on the complex plane represents the small interference stability degree of the power grid system.
Preferably, the calculating a comprehensive geometry controllable observability index according to the input signal and the output signal of the wide-area damping controller comprises:
Gcoi(i,j)＝goj(k)gck(k)，
wherein G iscoi(i, j) is a comprehensive geometric controllable observability index; goj(i) The observability index of the power grid system in the oscillation mode k is obtained; gck(i) The controllability index of the power grid system in the oscillation mode k is obtained; c. CjIs the jth row of the output matrix C; biIs the ith column of the input matrix B;
is cjAnd
the geometric angle of (A); theta (psi)i,bk) Is b iskAnd psikThe geometric angle of (c).
In step 102, according to the control loop, setting parameters of an artificial immune wide area control fixed link by a phase compensation method; wherein the parameters include: gain factor and a dc blocking time constant.
Preferably, the adjusting the parameters of the artificial immune wide area control fixed link by the phase compensation method includes:
wherein G iswpssA transfer function of an artificial immunity wide area control fixed link; k is the gain coefficient of the gain link; t isWIs a high pass filter coefficient; tm is the stopping time constant, m is 1,2,3,4, and T3＝T1，T4＝T2；fkThe oscillation frequency of the interval oscillation mode k corresponding to the preset frequency range is the oscillation frequency; wherein, the gain coefficient and the blocking time constant are determined according to the operation requirement of the power grid system and the specific damping control effect.
In the embodiment of the invention, the wide area PSS design idea based on the residue method is used for carrying out linearization processing on the power grid system in a typical operation mode and obtaining a system transfer function, calculating the residue of a specified mode and obtaining the phase of the mode to be compensated. Therefore, the transfer function of the artificial immune wide area control fixed link is:
wherein: the calculation formula of the relevant parameters of the lead-lag link is as follows:
wherein, T3＝T1，T4＝T2Tm is a stopping time constant; f. ofkThe oscillation frequency of the mode k is, and the mode k is an interval oscillation mode corresponding to the preset frequency range. The gain coefficient K and the stopping time constant are determined according to the system operation requirement and the specific damping control effect.
In step 103, the adjusted parameters are applied to the artificial immunity fixed control link, and the constraint ranges of the stimulation factors and the inhibition factors in the artificial immunity wide-area adaptive control link are set.
In the embodiment of the invention, the specific form of the adaptive immune control element is first derived. Assuming that the antigen concentration of the ith organism at the time T is w (T), the ith organism contains B cells and T cellsKAll antibody concentrations s (t) are expressed as:
S(t)＝TH(t)-TS(t)，
TH(t)＝m1iw(t)，
wherein, TH(T) T cells that are similar to activating immune effects; m is1iIs a stimulating factor; t isS(T) T cells resembling impaired control; m is2iIs an inhibitory factor; w (t-1) is the antigen concentration at the previous time. Different degrees of immune response also have some impact on self-antigens. The more stable the system is, TSThe larger the value, the more the cancellation T is meantHThe more obvious the immune effect, the more the body is forced to recover the original immune level.
For the artificial immune wide-area adaptive control link, the antibody concentration S (T) represents the output change quantity delta p (T) of the immune link, namely the output change quantity delta K and delta T of the controller parametersi(i ═ 1,2,3, 4); antigen concentration w (t) is system output, namely immune link input, and relative angular velocity delta omega between different units is selectedij(t) as an immune link input. The change Δ p of the ith controller unit parameter at time ti(t) can be expressed as:
the parameter update calculation formula for each controller unit i, which can be derived from this formula, is:
pi(t)＝pi-standard+Δpi(t)，
wherein p isi-standardThe calculated parameter of the ith controller unit is used for carrying out phase compensation on the system through the obtained control loop.
The variation of each control parameter is calculated by the formula and then is given to the fixed control link parameters so as to achieve the aim of dynamic adjustment.
In step 104, an objective function is determined according to a preset fault set, an artificial immunity wide area adaptive control link optimization model is established according to the objective function and the constraint ranges of the stimulation factor and the inhibition factor, and iterative training is performed on the artificial immunity wide area adaptive control link optimization model to determine the optimal values of the stimulation factor and the inhibition factor.
Preferably, the establishing of the artificial immunity wide-area adaptive control link optimization model comprises:
pi(t)＝pi-standard+Δpi(t)，
wherein p isi-standardGain K calculated for phase compensation of the system by the control loop obtained above, and lead-lag element Ti (i ═ 1,2,3,4), Δ pi(T) is the variation of the fixed link parameters at time T, namely, delta K (T), delta T1(t),ΔT2(t),ΔT3(t),ΔT4(t); pi (t) is the controller parameter updated by the immune adaptive link; Δ ωij(t) is the relative angular velocity between different units, i.e. the input signal for control; j is a target function determined according to a preset fault set; p is the fault category of the faults in the preset fault set; n is the number of the generator sets; delta omega (t) is the time-domain rotor angular speed deviation at the time t of the nth unit; alpha is alphapDetermining the weight coefficient according to the specific operation condition of the power grid system; m isminIs a stimulating factor m1iAnd the inhibitor m2iThe minimum value of the constraint range of (d); m ismaxIs a stimulating factor m1iAnd the inhibitor m2iIs the maximum value of the constraint range of (2).
Preferably, the iteratively training the artificial immune wide-area adaptive control element optimization model to determine the optimal values of the stimulation factor and the inhibition factor comprises:
randomly selecting values in a constraint range to assign values to each stimulating factor and each inhibiting factor in the artificial immune wide-area adaptive control link;
judging whether the objective function values corresponding to the current stimulation factors and the current inhibition factors are smaller than or equal to a preset objective function threshold, if so, determining the values of the current stimulation factors and the current inhibition factors as optimal values; otherwise, judging whether the current iteration number reaches a preset iteration number threshold value; if the current iteration times are equal to the preset iteration time threshold, selecting the values of the stimulation factor and the inhibition factor corresponding to the minimum objective function value as optimal values; if the current iteration times are smaller than the preset iteration time threshold, adjusting the values of each stimulation factor and each inhibition factor in the artificial immune wide-area adaptive control link according to a preset control strategy, and whether the objective function values corresponding to the current stimulation factors and the inhibition factors are smaller than or equal to the preset objective function threshold or not.
In the embodiment of the invention, the robustness of the system under uncertain operation modes such as unknown interference, faults and the like is enhanced by considering the fault set consisting of typical fault modes.
The objective function determined from the preset fault set may be expressed as:
based on the objective function and considering immune factor constraint boundary conditions, establishing the following artificial immune wide-area adaptive control link optimization model:
wherein J is an objective function; p is the fault category of the faults in the preset fault set; n is the number of the generator sets; delta omega (t) is the time-domain rotor angular speed deviation at the time t of the nth unit; alpha is alphapDetermining the weight coefficient according to the specific operation condition of the power grid system; m isminIs a stimulating factor m1iAnd the inhibitor m2iThe minimum value of the constraint range of (d); m ismaxIs a stimulating factor m1iAnd the inhibitor m2iIs the maximum value of the constraint range of (2).
Then, randomly selecting a value in a constraint range to assign values to each stimulation factor and inhibition factor in the artificial immune wide-area adaptive control link; judging whether the objective function values corresponding to the current stimulation factors and the current inhibition factors are smaller than or equal to a preset objective function threshold, if so, determining the values of the current stimulation factors and the current inhibition factors as optimal values; otherwise, judging whether the current iteration number reaches a preset iteration number threshold value; if the current iteration times are equal to the preset iteration time threshold, selecting the values of the stimulation factor and the inhibition factor corresponding to the minimum objective function value as optimal values; if the current iteration times are smaller than the preset iteration time threshold, adjusting the values of each stimulation factor and each inhibition factor in the artificial immune wide-area adaptive control link according to a preset control strategy, and whether the objective function values corresponding to the current stimulation factors and the inhibition factors are smaller than or equal to the preset objective function threshold or not.
Wherein, under the normal condition, the value ranges of the controller parameters K and Ti are [ 050%]And [ 01 ]]Thereby indirectly determining the stimulation factor m1iAnd inhibition of m2iThe value range of [ 050 ] can be determined according to experience]。
The following specifically exemplifies embodiments of the present invention
In an embodiment of the present invention, the architecture of the immune adaptive wide area damping controller is shown in fig. 2. Taking a two-zone four-machine system as shown in fig. 3 as an example, the method provided by the invention is used for controlling the wide-area damping controller, and the specific steps comprise:
the method comprises the following steps: and carrying out linearization processing on the tested power grid system, and establishing a mathematical model of a linear differential algebraic equation. According to the system state space expression, the observability index and the controllability index of the interval oscillation mode to be compensated are calculated, then the comprehensive geometric controllable observability index is calculated according to the observability index and the controllability index, and the result is shown in table 1. Selecting a strongly-related unit G1 with relatively best energy controllability as an installation place according to the results in the table 1, and selecting delta omega as a control signal13As a wide area control signal.
TABLE 1 comprehensive geometry controllable observability index
| Generator set | Δω13 | Δω14 | Δω23 | Δω24 |
| G1 | 1 | 0.7315 | 0.3529 | 0.4621 |
| G2 | 0.6849 | 0.2315 | 0.5068 | 0.9356 |
| G3 | 0.8274 | 0.7397 | 0.7397 | 0.2603 |
| G4 | 0.6862 | 0.3562 | 0.3562 | 0.8094 |
Step two: according to the determined control loop, the parameters of the immune fixed control link are calculated by a calculation residue phase compensation method as follows: k is 30, T1＝T3＝0.324，T2＝T40.212, where the high-pass filter coefficients take Tw 10. And then, small interference analysis is carried out, the characteristic value of the dominant mode is calculated to be-0.7631 + j4.5853, the damping ratio is 0.147, and the characteristic value is expressed as strong damping.
Step three: and applying the set parameters to the artificial immunity fixed control link, and setting the restraint range of the stimulation factor and the inhibition factor in the artificial immunity wide-area adaptive control link.
Step four: selecting the following two faults as a fault set under the normal operation condition of the system, determining an objective function, establishing an artificial immunity wide area adaptive control link optimization model according to the objective function and the constraint ranges of the stimulation factor and the inhibition factor, and performing iterative training on the artificial immunity wide area adaptive control link optimization model to determine the optimal values of the stimulation factor and the inhibition factor.
Wherein, two kinds of trouble are respectively: (1)1s, three-phase short circuit fault occurs in a No. 7 bus, 1.12s fault is removed, and 1.2s reclosing is successful; (2)1s, three-phase short circuit fault occurs on the No. 7 bus, and 1.12s fault is removed. The delay module z-1 takes the value of 100 ms.
The established multi-objective ITAE objective functions and constraint conditions are as follows:
when the parameters of the adaptive immune control link are optimized, the population number is set to be 50, the iteration times are 100, the average value is calculated by repeatedly running for 30 times, and the result is shown in table 2. And small interference analysis is carried out, the characteristic root of the obtained dominant mode is-0.7769 +4.6355j, the damping ratio is 0.165, and the damping characteristic of the low-frequency oscillation in the interval is further improved.
TABLE 2 adaptive Link immune parameter optimization results
| Parameter(s) | Numerical value | Parameter(s) | Numerical value |
| m11 | 32.112 | m12 | 17.002 |
| m21 | 0.144 | m22 | 4.266 |
| m31 | 0.282 | m32 | 6.658 |
| m42 | 5.480 | m42 | 4.308 |
| m51 | 12.076 | m52 | 5.052 |
By the immune self-adaptive wide area damping controller design method suitable for various faults and disturbances in the embodiment of the invention, wide area auxiliary excitation control can be performed.
In the following, it is assumed that nonlinear simulation analysis is performed under 4 different interference and fault conditions to check the effectiveness of the method provided by the embodiment of the present invention.
1) Failure 1
In the basic operation mode of the system, after 1s, 10% of step disturbance is applied to the input end of the excitation system of the unit G1, and the duration is 0.2 s. The comparison was made with a local PSS only, a wide-area PSS and an immune adaptive wide-area damping controller designed according to the present invention. The comparison results are shown in fig. 4 and 5, respectively. Fig. 4 is a G1 and G3 relative unit angular velocity response curve corresponding to the fault 1, and fig. 5 is a control parameter dynamic change curve corresponding to the fault 1. And (3) a dynamic change situation diagram of control parameters of the fixed link of the artificial immune wide area damping controller. It can be seen from fig. 4 and 5 that by dynamically adjusting the control parameters, the damping characteristic of the controller is enhanced, so that the interval low-frequency oscillation is rapidly suppressed.
2) Failure 2
And (3) the system normally operates, after 1s, a three-phase short-circuit fault occurs in the No. 7 bus, the fault is removed in 1.12s, and the 1.2s reclosing is successful. Fig. 6 is a graph of response curves of G1 and G3 relative to the unit angular velocity corresponding to fault 2. Fig. 7 is a graph showing the dynamic variation of the control parameter corresponding to the failure 2. It can be seen from fig. 6 and 7 that, for different faults, the control parameters adjusted by the immune adaptive link are also changed, so that the damping characteristic of the controller is enhanced, and the effect of suppressing the low-frequency oscillation in the interval is better.
3) Failure 3
After 1s, a three-phase short-circuit fault occurs in the No. 7 bus, and the fault is removed in 1.12s, so that the two-area connecting line is changed into a single-circuit operation state from a double-circuit line. Similarly, the G1 and G3 corresponding to the fault 3 are shown in the graph of the response curve of the angular speed of the unit and the dynamic change curve of the control parameter corresponding to the fault 3 as shown in fig. 8 and 9 respectively, and the effectiveness of the designed control method can be proved again through fig. 8 and 9.
4) And 4, fault: time-lag tolerant situation
Without any delay compensation, the controller time-lag robustness is tested, and 150ms delay is added to the wide-area signal. G1 and G3 relative unit angular velocity response curve graphs of the test system at fault 4, for example
Fig. 10 shows that the controller is designed to have a large dead-time margin, thus illustrating that the control system has dynamic compensation capability and is dynamically adjusted within a certain limit.
According to the test result, the adaptive wide-area damping controller control method based on the immune mechanism has the advantages of dynamic compensation effect and strong anti-interference capability. Compared with the traditional wide area PSS, the robustness of the system under uncertain conditions is improved, the response time of the system is shortened, the operation requirement of a power grid can be met, and the effectiveness and the applicability of the method provided by the invention are verified.
Fig. 11 is a schematic structural diagram of a control system 1200 of an adaptive wide-area damping controller based on an immunization scheme according to an embodiment of the invention. As shown in fig. 11, an embodiment of the invention provides a control system 1100 of an adaptive wide-area damping controller based on an immunization scheme, the system comprising: a control loop determination unit 1101, a parameter setting unit 1102, a setting unit 1103, and an optimum value determination unit 1104. The wide-area damping controller comprises an artificial immunity wide-area control fixing link and an artificial immunity wide-area adaptive control link.
Preferably, the control loop determining unit 1101 is configured to perform linearization processing on a power grid system model in a typical operation mode, calculate a comprehensive geometric controllable observability index according to an input signal and an output signal of the wide-area damping controller, and determine an optimal control location and a feedback signal according to the comprehensive geometric controllable observability index to determine a control loop.
Preferably, the control loop determining unit 1101 is configured to perform a linearization process on the power grid system model in a typical operation mode, and includes:
wherein, x (t), y (t), u (t) are the state, output and control vector of the power grid system in sequence, A is an n multiplied by n order state matrix; b is an n multiplied by p order input matrix; c is a q multiplied by n order output matrix, and the characteristic value calculated by the matrix A on the complex plane represents the small interference stability degree of the power grid system.
Preferably, the control loop determining unit 1101 calculates a comprehensive geometrically controllable observability indicator according to the input signal and the output signal of the wide-area damping controller, and includes:
Gcoi(i,j)＝goj(k)gck(k)，
wherein G iscoi(i, j) is a comprehensive geometric controllable observability index; goj(i) The observability index of the power grid system in the oscillation mode k is obtained; gck(i) The controllability index of the power grid system in the oscillation mode k is obtained; c. CjIs the jth row of the output matrix C; biIs the ith column of the input matrix B;
is cjAnd
the geometric angle of (A); theta (psi)i,bk) Is b iskAnd psikThe geometric angle of (c).
Preferably, the parameter setting unit 1102 is configured to set the parameter of the artificial immune wide area control fixed link according to the control loop by a phase compensation method; wherein the parameters include: gain factor and a dc blocking time constant.
Preferably, the parameter tuning unit 1102 tunes the parameters of the artificial immune wide area control fixed link through a phase compensation method, including:
wherein G iswpssA transfer function of an artificial immunity wide area control fixed link; k is the gain coefficient of the gain link; t isWIs a high pass filter coefficient; tm is the stopping time constant, m is 1,2,3,4, and T3＝T1，T4＝T2；fkThe oscillation frequency of the interval oscillation mode k corresponding to the preset frequency range is the oscillation frequency; wherein, the gain coefficient and the blocking time constant are determined according to the operation requirement of the power grid system and the specific damping control effect.
Preferably, the setting unit 1103 is configured to apply the set parameters to the artificial immunity fixed control unit, and set a constraint range of a stimulation factor and a suppression factor in the artificial immunity wide-area adaptive control unit.
Preferably, the optimal value determining unit 1104 is configured to determine an objective function according to a preset fault set, establish an artificial immune wide-area adaptive control link optimization model according to the objective function and constraint ranges of the stimulation factor and the suppression factor, and perform iterative training on the artificial immune wide-area adaptive control link optimization model to determine the optimal values of the stimulation factor and the suppression factor.
Preferably, the establishing of the artificial immunity wide-area adaptive control link optimization model comprises:
pi(t)＝pi-standard+Δpi(t)，
wherein p isi-standardGain K calculated for phase compensation of the system through the control loop obtained before and lead-lag element Ti(i＝1,2,3,4)，Δpi(T) is the variation of the fixed link parameters at time T, namely, delta K (T), delta T1(t),ΔT2(t),ΔT3(t),ΔT4(t)；pi(t) is the controller parameters updated by the immune adaptive link; Δ ωij(t) is the relative angular velocity between different units, i.e. the input signal for control; j is a target function determined according to a preset fault set; p is the fault category of the faults in the preset fault set; n is the number of the generator sets; delta omega (t) is the time-domain rotor angular speed deviation at the time t of the nth unit; alpha is alphapDetermining the weight coefficient according to the specific operation condition of the power grid system; m isminIs a stimulating factor m1iAnd the inhibitor m2iThe minimum value of the constraint range of (d); m ismaxIs a stimulating factor m1iAnd the inhibitor m2iIs the maximum value of the constraint range of (2).
Preferably, the optimal value determining unit 1104 iteratively trains the artificial immune wide-area adaptive control element optimization model to determine the optimal values of the stimulation factors and the inhibition factors, including:
randomly selecting values in a constraint range to assign values to each stimulating factor and each inhibiting factor in the artificial immune wide-area adaptive control link;
judging whether the objective function values corresponding to the current stimulation factors and the current inhibition factors are smaller than or equal to a preset objective function threshold, if so, determining the values of the current stimulation factors and the current inhibition factors as optimal values; otherwise, judging whether the current iteration number reaches a preset iteration number threshold value; if the current iteration times are equal to the preset iteration time threshold, selecting the values of the stimulation factor and the inhibition factor corresponding to the minimum objective function value as optimal values; if the current iteration times are smaller than the preset iteration time threshold, adjusting the values of each stimulation factor and each inhibition factor in the artificial immune wide-area adaptive control link according to a preset control strategy, and whether the objective function values corresponding to the current stimulation factors and the inhibition factors are smaller than or equal to the preset objective function threshold or not.
The control system 1100 of the adaptive wide-area damping controller based on the immune mechanism according to the embodiment of the present invention corresponds to the control method 100 of the adaptive wide-area damping controller based on the immune mechanism according to another embodiment of the present invention, and is not described herein again.
The invention has been described with reference to a few embodiments. However, other embodiments of the invention than the one disclosed above are equally possible within the scope of the invention, as would be apparent to a person skilled in the art from the appended patent claims.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a/an/the [ device, component, etc ]" are to be interpreted openly as referring to at least one instance of said device, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A control method of an adaptive wide-area damping controller based on an immune mechanism comprises an artificial immunity wide-area control fixed link and an artificial immunity wide-area adaptive control link; characterized in that the method comprises:
carrying out linearization processing on a power grid system model in a typical operation mode, calculating a comprehensive geometric controllable observability index according to an input signal and an output signal of a wide-area damping controller, and determining an optimal control place and a feedback signal according to the comprehensive geometric controllable observability index so as to determine a control loop;
according to the control loop, setting parameters of an artificial immune wide area control fixed link by a phase compensation method; wherein the parameters include: gain factor and a dc blocking time constant;
applying the set parameters to the artificial immunity wide area control fixing link, and setting the restraint range of the stimulation factor and the inhibition factor in the artificial immunity wide area adaptive control link;
determining a target function according to a preset fault set, establishing an artificial immunity wide area adaptive control link optimization model according to the target function and the constraint ranges of the stimulation factor and the inhibition factor, and performing iterative training on the artificial immunity wide area adaptive control link optimization model to determine the optimal values of the stimulation factor and the inhibition factor;
the establishing of the artificial immunity wide-area adaptive control link optimization model comprises the following steps:
pi(t)＝pi-standard+Δpi(t)，
wherein p isi-standardGain K calculated for phase compensation of the system through the control loop obtained before and lead-lag element Ti(i＝1,2,3,4)，Δpi(T) is the variation of the fixed link parameters at time T, namely, delta K (T), delta T1(t),ΔT2(t),ΔT3(t),ΔT4(t)；pi(t) is the controller parameters updated by the immune adaptive link; Δ ωij(t) is the relative angular velocity between different units, i.e. the input signal for control; j is a target function determined according to a preset fault set; p is the fault category of the faults in the preset fault set; n is the number of the generator sets; delta omega (t) is the time-domain rotor angular speed deviation at the time t of the nth unit; alpha is alphapDetermining the weight coefficient according to the specific operation condition of the power grid system; m isminIs a stimulating factor m1iAnd the inhibitor m2iThe minimum value of the constraint range of (d); m ismaxIs a stimulating factor m1iAnd the inhibitor m2iIs the maximum value of the constraint range of (2).
2. The method of claim 1, wherein linearizing the model of the grid system in the typical operating mode comprises:
wherein, x (t), y (t), u (t) are the state, output and control vector of the power grid system in sequence, A is an n multiplied by n order state matrix; b is an n multiplied by p order input matrix; c is a q multiplied by n order output matrix, and the characteristic value calculated by the matrix A on the complex plane represents the small interference stability degree of the power grid system.
3. The method of claim 1, wherein calculating a synthetic geometrically controllable observability indicator from the input signal and the output signal of the wide-area damping controller comprises:
Gcoi(i,j)＝goj(k)gck(k)，
wherein G iscoi(i, j) is a comprehensive geometric controllable observability index; goj(i) The observability index of the power grid system in the oscillation mode k is obtained; gck(i) The controllability index of the power grid system in the oscillation mode k is obtained; c. CjIs the jth row of the output matrix C; biIs the ith column of the input matrix B;
is cjAnd
the geometric angle of (A); theta (psi)k,bi) Is b isiAnd psikThe geometric angle of (c).
4. The method of claim 1, wherein the adjusting parameters of the artificial immune wide area control fixed link by the phase compensation method comprises:
wherein G iswpssA transfer function of an artificial immunity wide area control fixed link; k is the gain coefficient of the gain link; t isWIs a high pass filter coefficient; tm is the stopping time constant, m is 1,2,3,4, and T3＝T1，T4＝T2；fkThe oscillation frequency of the interval oscillation mode k corresponding to the preset frequency range is the oscillation frequency; wherein, the gain coefficient and the blocking time constant are determined according to the operation requirement of the power grid system and the specific damping control effect.
5. The method of claim 1, wherein iteratively training the artificial immune wide-area adaptive control element optimization model to determine optimal values for the stimulation and inhibition factors comprises:
randomly selecting values in a constraint range to assign values to each stimulating factor and each inhibiting factor in the artificial immune wide-area adaptive control link;
judging whether the objective function values corresponding to the current stimulation factors and the current inhibition factors are smaller than or equal to a preset objective function threshold, if so, determining the values of the current stimulation factors and the current inhibition factors as optimal values; otherwise, judging whether the current iteration number reaches a preset iteration number threshold value; if the current iteration times are equal to the preset iteration time threshold, selecting the values of the stimulation factor and the inhibition factor corresponding to the minimum objective function value as optimal values; if the current iteration times are smaller than the preset iteration time threshold, adjusting the values of each stimulation factor and each inhibition factor in the artificial immune wide-area adaptive control link according to a preset control strategy, and whether the objective function values corresponding to the current stimulation factors and the inhibition factors are smaller than or equal to the preset objective function threshold or not.
6. A control system of an adaptive wide-area damping controller based on an immunization mechanism comprises an artificial immunization wide-area control fixed link and an artificial immunization wide-area adaptive control link; characterized in that the system comprises:
the control loop determining unit is used for carrying out linearization processing on a power grid system model in a typical operation mode, calculating a comprehensive geometric controllable observability index according to an input signal and an output signal of the wide-area damping controller, and determining an optimal control place and a feedback signal according to the comprehensive geometric controllable observability index so as to determine a control loop;
the parameter setting unit is used for setting parameters of the artificial immune wide area control fixed link through a phase compensation method according to the control loop; wherein the parameters include: gain factor and a dc blocking time constant;
the setting unit is used for applying the set parameters to the artificial immunity wide area control fixing link and setting the constraint range of the stimulation factor and the inhibition factor in the artificial immunity wide area adaptive control link;
the system comprises an optimal value determining unit, a fault analysis unit and a fault analysis unit, wherein the optimal value determining unit is used for determining an objective function according to a preset fault set, establishing an artificial immunity wide area adaptive control link optimization model according to the objective function and the constraint ranges of a stimulation factor and a suppression factor, and performing iterative training on the artificial immunity wide area adaptive control link optimization model to determine the optimal values of the stimulation factor and the suppression factor;
the establishing of the artificial immunity wide-area adaptive control link optimization model comprises the following steps:
pi(t)＝pi-standard+Δpi(t)，
wherein p isi-standardGain K calculated for phase compensation of the system through the control loop obtained before and lead-lag element Ti(i＝1,2,3,4)，Δpi(t) is a fixed link parameter at time tOf change, i.e. Δ K (T), Δ T1(t),ΔT2(t),ΔT3(t),ΔT4(t)；pi(t) is the controller parameters updated by the immune adaptive link; Δ ωij(t) is the relative angular velocity between different units, i.e. the input signal for control; j is a target function determined according to a preset fault set; p is the fault category of the faults in the preset fault set; n is the number of the generator sets; delta omega (t) is the time-domain rotor angular speed deviation at the time t of the nth unit; alpha is alphapDetermining the weight coefficient according to the specific operation condition of the power grid system; m isminIs a stimulating factor m1iAnd the inhibitor m2iThe minimum value of the constraint range of (d); m ismaxIs a stimulating factor m1iAnd the inhibitor m2iIs the maximum value of the constraint range of (2).
7. The system of claim 6, wherein the control loop determination unit linearizes the model of the power grid system in a typical operating mode, comprising:
wherein, x (t), y (t), u (t) are the state, output and control vector of the power grid system in sequence, A is an n multiplied by n order state matrix; b is an n multiplied by p order input matrix; c is a q multiplied by n order output matrix, and the characteristic value calculated by the matrix A on the complex plane represents the small interference stability degree of the power grid system.
8. The system of claim 6, wherein the control loop determination unit calculates a synthetic geometrically controllable observability indicator from the input signal and the output signal of the wide-area damping controller, comprising:
Gcoi(i,j)＝goj(k)gck(k)，
wherein G iscoi(i, j) is a comprehensive geometric controllable observability index; goj(i) The observability index of the power grid system in the oscillation mode k is obtained; gck(i) The controllability index of the power grid system in the oscillation mode k is obtained; c. CjIs the jth row of the output matrix C; biIs the ith column of the input matrix B;
is cjAnd
the geometric angle of (A); theta (psi)k,bi) Is b isiAnd chikThe geometric angle of (c).
9. The system of claim 6, wherein the parameter tuning unit tunes the parameters of the artificial immune wide area control fixed link through a phase compensation method, and comprises:
wherein G iswpssA transfer function of an artificial immunity wide area control fixed link; k is the gain coefficient of the gain link; t isWIs a high pass filter coefficient; tm is the stopping time constant, m is 1,2,3,4, and T3＝T1，T4＝T2；fkThe oscillation frequency of the interval oscillation mode k corresponding to the preset frequency range is the oscillation frequency; wherein,and determining the gain coefficient and the blocking time constant according to the operation requirement of the power grid system and the specific damping control effect.
10. The system of claim 6, wherein the optimal value determining unit iteratively trains the artificial immune wide-area adaptive control element optimization model to determine the optimal values of the stimulation factors and the inhibition factors, and comprises:
randomly selecting values in a constraint range to assign values to each stimulating factor and each inhibiting factor in the artificial immune wide-area adaptive control link;
judging whether the objective function values corresponding to the current stimulation factors and the current inhibition factors are smaller than or equal to a preset objective function threshold, if so, determining the values of the current stimulation factors and the current inhibition factors as optimal values; otherwise, judging whether the current iteration number reaches a preset iteration number threshold value; if the current iteration times are equal to the preset iteration time threshold, selecting the values of the stimulation factor and the inhibition factor corresponding to the minimum objective function value as optimal values; if the current iteration times are smaller than the preset iteration time threshold, adjusting the values of each stimulation factor and each inhibition factor in the artificial immune wide-area adaptive control link according to a preset control strategy, and whether the objective function values corresponding to the current stimulation factors and the inhibition factors are smaller than or equal to the preset objective function threshold or not.
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