CN114006387B - Self-adaptive frequency subsynchronous oscillation suppression method and system based on multi-branch impedance - Google Patents

Self-adaptive frequency subsynchronous oscillation suppression method and system based on multi-branch impedance Download PDF

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CN114006387B
CN114006387B CN202111402110.7A CN202111402110A CN114006387B CN 114006387 B CN114006387 B CN 114006387B CN 202111402110 A CN202111402110 A CN 202111402110A CN 114006387 B CN114006387 B CN 114006387B
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machine side
control
fuzzy
oscillation frequency
control parameter
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CN114006387A (en
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刘其辉
田若菡
贾瑞媛
郭小江
汤海雁
申旭辉
李铮
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Huaneng Clean Energy Research Institute
North China Electric Power University
Huaneng Group Technology Innovation Center Co Ltd
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Huaneng Clean Energy Research Institute
North China Electric Power University
Huaneng Group Technology Innovation Center Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Control Of Eletrric Generators (AREA)

Abstract

The invention relates to a self-adaptive frequency subsynchronous oscillation suppression method and a self-adaptive frequency subsynchronous oscillation suppression system based on multi-branch impedance, which belong to the field of double-fed wind turbines, wherein a particle swarm algorithm is adopted to carry out simulation solution on a double-fed wind turbine system, control parameters of a machine side converter under oscillation frequency corresponding to each control condition are obtained, a fuzzy controller based on a fuzzy control rule is constructed, real-time oscillation frequency of the double-fed wind turbine system when subsynchronous oscillation occurs is input into the fuzzy controller based on the fuzzy control rule, real-time control parameters of the machine side converter are output, fuzzy control is adopted on the control parameters, and the suppression effect of the self-adaptive frequency is realized, so that the optimal suppression effect can be achieved under each oscillation frequency.

Description

Self-adaptive frequency subsynchronous oscillation suppression method and system based on multi-branch impedance
Technical Field
The invention relates to the field of doubly-fed wind turbines, in particular to a self-adaptive frequency subsynchronous oscillation suppression method and system based on multi-branch impedance.
Background
Wind energy is used as clean and renewable energy sources to be greatly developed, but under the series compensation grid-connected condition, subsynchronous oscillation of the doubly-fed wind turbine generator occurs, so that the large-area wind turbine generator is separated from a power grid, and the threat to the power grid is great. To avoid this effect, quick and effective measures are required to suppress the subsynchronous oscillation.
At present, a double-fed wind turbine generator subsynchronous oscillation suppression strategy based on multi-branch impedance remodeling is provided for solving the subsynchronous oscillation problem, but simulation discovers that in the suppression strategy, a fixed value pair is selected for control parameters in the strategy, so that the suppression effect is not generated, waveforms are dispersed, a good suppression effect cannot be achieved, and serious faults are caused to a power system.
Disclosure of Invention
The invention aims to provide a self-adaptive frequency subsynchronous oscillation suppression method and a system based on multi-branch impedance, so that an optimal suppression effect can be achieved under each oscillation frequency.
In order to achieve the above object, the present invention provides the following solutions:
a method of adaptive frequency subsynchronous oscillation suppression based on multi-branch impedance, the method comprising:
respectively carrying out simulation solution on the doubly-fed wind turbine generator system by adopting a particle swarm algorithm under different control conditions to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition; the control conditions comprise wind speed, grid strength and serial compensation; virtual impedance control is added to a machine side converter and a network side converter of the doubly-fed wind generating set system; the control parameters comprise a machine side resistance remodeling control parameter and a machine side reactance remodeling control parameter;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, formulating a fuzzy control rule between the oscillation frequency and the control parameters, and constructing a fuzzy controller based on the fuzzy control rule;
acquiring real-time oscillation frequency of a doubly-fed wind turbine generator system when subsynchronous oscillation occurs;
and inputting the real-time oscillation frequency into a fuzzy controller based on the fuzzy control rule, and outputting real-time control parameters of the side converter.
Optionally, the particle swarm algorithm is adopted to respectively perform simulation solution on the doubly-fed wind turbine generator system under different control conditions to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, and the method specifically comprises the following steps:
constructing an objective function asThe constraint is Kr_ rsc>0 and Kx_ rsc>0; wherein sigma is the total overshoot of the oscillating power of the wind turbine generator relative to the steady-state value of the oscillating power, P (t) is the instantaneous output power of the wind turbine generator, and P N (V w ) To be in a specific state V w Steady-state output power, t, of corresponding wind turbine generator i For the start time, t i +T is the termination time, T is the time period, kr_ rsc is the machine side resistance remodeling control parameter, kx_ rsc is the machine side reactance remodeling control parameter;
simulating the doubly-fed wind turbine generator system under different control conditions to obtain instantaneous output power of a plurality of wind turbine generators;
and carrying out optimizing solution on the objective function by adopting a particle swarm algorithm based on constraint conditions according to the instantaneous output power of the wind turbines to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition.
Optionally, the step of formulating a fuzzy control rule between the oscillation frequency and the control parameter according to the control parameter of the machine side converter under the oscillation frequency corresponding to each control condition, and constructing a fuzzy controller based on the fuzzy control rule specifically includes:
determining the oscillation frequency as an input variable of the fuzzy controller, and determining a control parameter of the machine side converter as an output variable of the fuzzy controller;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, the basic domain and the fuzzy domain of the input variable and the basic domain and the fuzzy domain of the output variable are respectively obtained;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, respectively determining that a fuzzy subset of input variables is { SS, S, ME, B and BB }, a fuzzy subset of machine side resistance remodeling control parameters is { LL, L, MM, M, H and HH }, and a fuzzy subset of machine side reactance remodeling control parameters is { Z, ZZ, L 'L', L ', M' M ', M', H ', H' }; wherein SS, S, ME, B, BB are respectively oscillation frequencies which are sequentially increased from small to large; LL, L, MM, M, H, HH are values of the machine side resistance remodeling control parameters which increase in sequence from small to large respectively; z, ZZ, L 'L', M 'M', H 'H' are values of machine side reactance remodeling control parameters which are sequentially increased from small to large respectively;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, adopting a triangle membership functionRespectively used as membership functions of an input variable and an output variable; wherein a and c are the values of two feet of a triangle in the triangle membership function curve, b is the value of a peak of the triangle in the triangle membership function curve, x is an input variable or an output variable, and mu is membership;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, the change trend of the control parameters of the machine side converter along with the change of the oscillation frequency is obtained;
according to the change trend, a fuzzy control rule between the oscillation frequency and the control parameter is formulated;
and constructing a fuzzy controller based on the fuzzy control rule according to the basic domain and the fuzzy domain of the input variable, the basic domain and the fuzzy domain of the output variable, the fuzzy subset of the input variable, the fuzzy subset of the machine side resistance remodeling control parameter, the fuzzy subset of the machine side reactance remodeling control parameter, the membership function of the input variable and the membership function of the output variable.
Optionally, the change trend of the control parameter of the machine side converter along with the change of the oscillation frequency is that the machine side resistance remodelling control parameter gradually decreases and then tends to be stable along with the increase of the oscillation frequency, and the machine side reactance remodelling control parameter gradually increases and then tends to be stable.
Optionally, the fuzzy control rule between the oscillation frequency and the control parameter is:
when the oscillation frequency is SS, the value of the machine side resistance remodeling control parameter is HH, and the value of the machine side reactance remodeling control parameter is Z;
when the oscillation frequency is S, the value of the machine side resistance remodeling control parameter is MM, and the value of the machine side reactance remodeling control parameter is M 'M';
when the oscillation frequency is ME, the value of the machine side resistance remodeling control parameter is LL, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is B, the value of the machine side resistance remodeling control parameter is L, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is BB, the value of the machine side resistance remodeling control parameter is M, and the value of the machine side reactance remodeling control parameter is H 'H'.
An adaptive frequency subsynchronous oscillation suppression system based on multi-branch impedance, the system comprising:
the simulation module is used for respectively carrying out simulation solution on the doubly-fed wind turbine generator system by adopting a particle swarm algorithm under different control conditions to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition; the control conditions comprise wind speed, grid strength and serial compensation; virtual impedance control is added to a machine side converter and a network side converter of the doubly-fed wind generating set system; the control parameters comprise a machine side resistance remodeling control parameter and a machine side reactance remodeling control parameter;
the fuzzy controller construction module is used for formulating a fuzzy control rule between the oscillation frequency and the control parameter according to the control parameter of the machine side converter under the oscillation frequency corresponding to each control condition and constructing a fuzzy controller based on the fuzzy control rule;
the real-time oscillation frequency acquisition module is used for acquiring the real-time oscillation frequency of the doubly-fed wind turbine generator system when subsynchronous oscillation occurs;
and the real-time control parameter output module is used for inputting the real-time oscillation frequency into the fuzzy controller based on the fuzzy control rule and outputting real-time control parameters of the side converter.
Optionally, the simulation module specifically includes:
an objective function construction submodule for constructing an objective function asThe constraint is Kr_ rsc>0 and Kx_ rsc>0; wherein sigma is the total overshoot of the oscillating power of the wind turbine generator relative to the steady-state value of the oscillating power, P (t) is the instantaneous output power of the wind turbine generator, and P N (V w ) To be in a specific state V w Steady-state output power, t, of corresponding wind turbine generator i For the start time, t i +T is the termination time, T is the time period, kr_ rsc is the machine side resistance remodeling control parameter, kx_ rsc is the machine side reactance remodeling control parameter;
the instantaneous output power obtaining submodule is used for simulating the doubly-fed wind turbine generator system under different control conditions to obtain instantaneous output power of a plurality of wind turbine generators;
and the optimizing sub-module is used for optimizing and solving the objective function by adopting a particle swarm algorithm based on constraint conditions according to the instantaneous output power of the wind turbines to obtain the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition.
Optionally, the fuzzy controller building module specifically includes:
the variable determining submodule is used for determining the oscillation frequency as an input variable of the fuzzy controller, and the control parameter of the machine side converter is determined as an output variable of the fuzzy controller;
the domain acquisition sub-module is used for respectively acquiring a basic domain and a fuzzy domain of an input variable and a basic domain and a fuzzy domain of an output variable according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the fuzzy subset determining submodule is used for respectively determining that a fuzzy subset of input variables is { SS, S, ME, B and BB }, a fuzzy subset of machine side resistance remodeling control parameters is { LL, L, MM, M, H and HH }, and a fuzzy subset of machine side reactance remodeling control parameters is { Z, ZZ, L 'L', L ', M' M ', M', H 'H' }; wherein SS, S, ME, B, BB are respectively oscillation frequencies which are sequentially increased from small to large; LL, L, MM, M, H, HH are values of the machine side resistance remodeling control parameters which increase in sequence from small to large respectively; z, ZZ, L 'L', M 'M', H 'H' are values of machine side reactance remodeling control parameters which are sequentially increased from small to large respectively;
the membership function determining submodule is used for adopting a triangular membership function according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control conditionRespectively used as membership functions of an input variable and an output variable; wherein a and c are the values of two feet of a triangle in the triangle membership function curve, b is the value of a peak of the triangle in the triangle membership function curve, x is an input variable or an output variable, and mu is membership;
the change trend obtaining submodule is used for obtaining the change trend of the control parameters of the machine side converter along with the change of the oscillation frequency according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the fuzzy control rule making sub-module is used for making a fuzzy control rule between the oscillation frequency and the control parameter according to the change trend;
the fuzzy controller construction submodule is used for constructing the fuzzy controller based on the fuzzy control rule according to the basic argument and the fuzzy argument of the input variable, the basic argument and the fuzzy argument of the output variable, the fuzzy subset of the input variable, the fuzzy subset of the machine side resistance remodeling control parameter, the fuzzy subset of the machine side reactance remodeling control parameter, the membership function of the input variable and the membership function of the output variable.
Optionally, the change trend of the control parameter of the machine side converter along with the change of the oscillation frequency is that the machine side resistance remodelling control parameter gradually decreases and then tends to be stable along with the increase of the oscillation frequency, and the machine side reactance remodelling control parameter gradually increases and then tends to be stable.
Optionally, the fuzzy control rule between the oscillation frequency and the control parameter is:
when the oscillation frequency is SS, the value of the machine side resistance remodeling control parameter is HH, and the value of the machine side reactance remodeling control parameter is Z;
when the oscillation frequency is S, the value of the machine side resistance remodeling control parameter is MM, and the value of the machine side reactance remodeling control parameter is M 'M';
when the oscillation frequency is ME, the value of the machine side resistance remodeling control parameter is LL, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is B, the value of the machine side resistance remodeling control parameter is L, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is BB, the value of the machine side resistance remodeling control parameter is M, and the value of the machine side reactance remodeling control parameter is H 'H'.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a self-adaptive frequency subsynchronous oscillation suppression method and a self-adaptive frequency subsynchronous oscillation suppression system based on multi-branch impedance.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for suppressing adaptive frequency subsynchronous oscillation based on multi-branch impedance provided by the invention;
FIG. 2 is a schematic diagram of a fuzzy controller according to the present invention;
FIG. 3 is a graph of membership function provided by the present invention; fig. 3 (a) is a membership function graph of oscillation frequency, fig. 3 (b) is a membership function graph of machine side resistance remodeling control parameter, and fig. 3 (c) is a membership function graph of machine side reactance remodeling control parameter;
FIG. 4 is a schematic diagram of an application of the fuzzy controller according to the present invention;
FIG. 5 is a graph showing the comparison of suppression effects under fuzzy control and fixed control parameters provided by the present invention; fig. 5 (a) is a graph showing a suppression effect at an oscillation frequency of 4Hz, fig. 5 (b) is a graph showing a suppression effect at an oscillation frequency of 6Hz, fig. 5 (c) is a graph showing a suppression effect at an oscillation frequency of 8Hz, fig. 5 (d) is a graph showing a suppression effect at an oscillation frequency of 10Hz, and fig. 5 (e) is a graph showing a suppression effect at an oscillation frequency of 12 Hz.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a self-adaptive frequency subsynchronous oscillation suppression method and a system based on multi-branch impedance, so that an optimal suppression effect can be achieved under each oscillation frequency.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
The doubly-fed wind motor comprises a controlled DFIG (Double-fed induction generator) system and a grid-side converter, virtual impedance control is added in a side converter RSC and a grid-side converter GSC of the doubly-fed wind motor to change the equivalent impedance of the doubly-fed wind power generation system, and therefore the quick and effective suppression of subsynchronous oscillation is achieved.
In the double-fed wind turbine generator subsynchronous oscillation suppression strategy based on multi-branch impedance remodeling, the new voltage command value is equivalent to that virtual impedance Z is respectively added to two branches of RSC and GSC rsc_ssr And Z gsc_ssr Thereby changing the equivalent impedance of the doubly-fed wind power generation system. However, when a pair of fixed values is given to the two additional control parameters in the simulation process, the suppression effect can be achieved under certain oscillation frequencies, but when the two additional control parameters are set to be a pair of fixed parameters, the two additional control parameters are not suppressed, but the waveforms are confused, and serious faults are caused to the power system under relatively high oscillation frequencies.
The four additional control parameters of the additional damping control model in the double-fed wind turbine generator set subsynchronous oscillation suppression strategy based on multi-branch impedance remodeling are Kx_rsc, kr_rsc, kx_gsc and Kr_ gsc respectively, and according to the current existing research, the influence of the control parameters Krp and Kri on the side of the machine side RSC on the real part of the system impedance is far greater than other parameters, namely the influence on the subsynchronous oscillation is far greater than other parameters, and the two parameters are used as main control parameters, so the invention only controls the two additional control parameters Kx_rsc and Kr_ RSC of the machine side converter. At each oscillation frequency, kr_ rsc and kx_ rsc can be adjusted to achieve the best suppression effect.
The invention provides a multi-branch impedance remodeling-based double-fed wind turbine generator subsynchronous oscillation suppression strategy, and provides a multi-branch impedance-based self-adaptive frequency subsynchronous oscillation suppression method, as shown in fig. 1, which comprises the following steps:
step 101, respectively carrying out simulation solution on a doubly-fed wind turbine generator system by adopting a particle swarm algorithm under different control conditions to obtain control parameters of a machine side converter under the oscillation frequency corresponding to each control condition; the control conditions comprise wind speed, grid strength and serial compensation; virtual impedance control is added to a machine side converter and a network side converter of the doubly-fed wind generating set system; the control parameters include a machine side resistance remodeling control parameter and a machine side reactance remodeling control parameter.
First, to adapt the established fuzzy rules to most situations, it is necessary to simulate the system under different conditions (different wind speeds, different grid strengths, different series supplements) based on experience derived from a large number of simulations.
The method comprises the following specific steps:
constructing an objective function asThe constraint is Kr_ rsc>0 and Kx_ rsc>0; wherein sigma is the total overshoot of the oscillating power of the wind turbine generator relative to the steady-state value of the oscillating power, P (t) is the instantaneous output power of the wind turbine generator, and P N (V w ) To be in a specific state V w Steady-state output power, t, of corresponding wind turbine generator i For the start time, t i +T is the termination time, T is the time period, kr_ rsc is the machine side resistance remodeling control parameter, kx_ rsc is the machine side reactance remodeling control parameter;
simulating the doubly-fed wind turbine generator system under different control conditions to obtain instantaneous output power of a plurality of wind turbine generators; under different wind speeds and different power grid intensities, particle swarm optimization (parameter optimization) is carried out on two parameters of Kr_ rsc and Kx_ rsc in a model at intervals of 4% of serial supplements, and each serial supplement necessarily corresponds to a corresponding oscillation frequency, so that the optimal control parameters under the fixed subsynchronous oscillation frequencies under different wind speeds and different power grid intensities are obtained later;
and carrying out optimizing solution on the objective function by adopting a particle swarm algorithm based on constraint conditions according to the instantaneous output power of the wind turbines to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition. In the optimizing process, the minimum objective function is ensured, each condition has corresponding oscillation frequency, the objective function under the corresponding oscillation frequency is optimized, the algorithm outputs the optimal Kr_ rsc and Kx_ rsc under the corresponding oscillation frequency, namely, in the optimal state, the total overshoot of the oscillation power of the wind turbine generator set relative to the steady state value is minimum during oscillation.
And 102, formulating a fuzzy control rule between the oscillation frequency and the control parameter according to the control parameter of the machine side converter under the oscillation frequency corresponding to each control condition, and constructing a fuzzy controller based on the fuzzy control rule.
The method specifically comprises the following steps:
(1) The oscillation frequency is determined as an input variable of the fuzzy controller and the control parameter of the machine side converter is determined as an output variable of the fuzzy controller, as shown in fig. 2. Fuzzy in fig. 2 represents blurring.
(2) According to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, the basic domain and the fuzzy domain of the input variable and the basic domain and the fuzzy domain of the output variable are respectively obtained;
the results of the optimization of the control parameters are shown in the following table:
TABLE 1 optimization results of control parameters
The fundamental domain of oscillation frequency f is set to [4,12] Hz and the fuzzy domain is {4,6,8, 10, 12}. The basic argument of Kr_ rsc is set to [0.28,0.38], and the fuzzy argument is {0,1,2,3,4,5}. Kx_ rsc: the basic argument is set to [0.45,0.8] Hz, and the fuzzy argument is {0,1,2,3,4,5,6,7}.
(3) According to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, respectively determining that a fuzzy subset of input variables is { SS, S, ME, B and BB }, a fuzzy subset of machine side resistance remodeling control parameters is { LL, L, MM, M, H and HH }, and a fuzzy subset of machine side reactance remodeling control parameters is { Z, ZZ, L 'L', L ', M' M ', M', H ', H' }; wherein SS, S, ME, B, BB are respectively oscillation frequencies which are sequentially increased from small to large; LL, L, MM, M, H, HH are values of the machine side resistance remodeling control parameters which increase in sequence from small to large respectively; z, ZZ, L 'L', M 'M', H 'H' are values of machine side reactance remodeling control parameters which are sequentially increased from small to large respectively;
(4) According to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, adopting a triangle membership functionRespectively used as membership functions of an input variable and an output variable; wherein a and c are the values of two feet of a triangle in the triangle membership function curve, b is the value of a peak of the triangle in the triangle membership function curve, x is an input variable or an output variable, and mu is membership;
the membership function graphs of the input variable and the output variable are shown in figure 3.
(5) According to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, the change trend of the control parameters of the machine side converter along with the change of the oscillation frequency is obtained;
as can be seen from table 1, kr_ rsc gradually decreases and becomes stable with increasing oscillation frequency, and kx_ rsc gradually increases and becomes stable.
(6) According to the change trend, a fuzzy control rule between the oscillation frequency and the control parameter is formulated;
the fuzzy control rule is as follows:
when the oscillation frequency is SS, the value of the machine side resistance remodeling control parameter is HH, and the value of the machine side reactance remodeling control parameter is Z;
when the oscillation frequency is S, the value of the machine side resistance remodeling control parameter is MM, and the value of the machine side reactance remodeling control parameter is M 'M';
when the oscillation frequency is ME, the value of the machine side resistance remodeling control parameter is LL, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is B, the value of the machine side resistance remodeling control parameter is L, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is BB, the value of the machine side resistance remodeling control parameter is M, and the value of the machine side reactance remodeling control parameter is H 'H'.
Table 2 fuzzy control rules
Oscillation frequency Kr_rsc Kx_rsc
SS HH Z
S MM M'M'
ME LL H'
B L H'
BB M H'H'
In the invention, only 4-12Hz of oscillation frequency is considered, so that the oscillation below 4Hz rarely occurs, and the oscillation with a larger frequency above 12Hz can also formulate a fuzzy rule according to the method to carry out fuzzy control.
(7) And constructing a fuzzy controller based on a fuzzy control rule according to the basic domain and the fuzzy domain of the input variable, the basic domain and the fuzzy domain of the output variable, the fuzzy subset of the input variable, the fuzzy subset of the machine side resistance remodeling control parameter, the fuzzy subset of the machine side reactance remodeling control parameter, the membership function of the input variable and the membership function of the output variable.
And step 103, obtaining the real-time oscillation frequency of the doubly-fed wind turbine system when subsynchronous oscillation occurs.
And 104, inputting the real-time oscillation frequency into a fuzzy controller based on a fuzzy control rule, and outputting real-time control parameters of the side converter.
Referring to fig. 4, the fuzzy control rule is input into the fuzzy control module, the input of the fuzzy control module is the oscillation frequency, and the output is two additional control parameters of kr_ rsc and kx_ rsc, so that when the system generates subsynchronous oscillation, the system detects the oscillation frequency and inputs the oscillation frequency into the fuzzy control module, and the two additional control parameters in the system are directly changed so as to reach the optimal inhibition state.
If the additional impedance is modeled and several additional parameters are extricated, however, the method is particularly complex due to too many variables, and the control effect of classical control theory and modern control theory is not ideal for nonlinear systems. The invention adopts fuzzy control, and has the advantages that a complex mathematical model is not required to be established in the process of formulating the fuzzy rules, the robustness and the adaptability can meet the control requirement, a plurality of rules are summarized according to the simulation result, and the fuzzy controller is designed according to the rules.
In the additional control strategy, compared with the suppression effect under the fixed parameters before, the suppression method can realize the suppression effect of the self-adaptive frequency, and the suppression effect under the fixed control parameters is better than the suppression effect under the fixed control parameters, and is shown in fig. 5.
The invention is carried out on a subsynchronous oscillation suppression strategy of the double-fed wind turbine based on multi-branch impedance remodeling, and fuzzy control is adopted for control parameters in the suppression strategy, so that an optimal suppression effect can be achieved under each oscillation frequency.
The invention also provides a self-adaptive frequency subsynchronous oscillation suppression system based on the multi-branch impedance, which comprises:
the simulation module is used for respectively carrying out simulation solution on the doubly-fed wind turbine generator system by adopting a particle swarm algorithm under different control conditions to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition; the control conditions comprise wind speed, grid strength and serial compensation; virtual impedance control is added to a machine side converter and a network side converter of the doubly-fed wind generating set system; the control parameters comprise a machine side resistance remodeling control parameter and a machine side reactance remodeling control parameter;
the fuzzy controller construction module is used for formulating a fuzzy control rule between the oscillation frequency and the control parameter according to the control parameter of the machine side converter under the oscillation frequency corresponding to each control condition and constructing a fuzzy controller based on the fuzzy control rule;
the real-time oscillation frequency acquisition module is used for acquiring the real-time oscillation frequency of the doubly-fed wind turbine generator system when subsynchronous oscillation occurs;
and the real-time control parameter output module is used for inputting the real-time oscillation frequency into the fuzzy controller based on the fuzzy control rule and outputting real-time control parameters of the side converter.
The simulation module specifically comprises:
an objective function construction submodule for constructing an objective function asThe constraint is Kr_ rsc>0 and Kx_ rsc>0; wherein sigma is the total overshoot of the oscillating power of the wind turbine generator relative to the steady-state value of the oscillating power, P (t) is the instantaneous output power of the wind turbine generator, and P N (V w ) To be in a specific state V w Steady-state output power, t, of corresponding wind turbine generator i For the start time, t i +T is the termination time, T is the time period, kr_ rsc is the machine side resistance remodeling control parameter, kx_ rsc is the machine side reactance remodeling control parameter;
the instantaneous output power obtaining submodule is used for simulating the doubly-fed wind turbine generator system under different control conditions to obtain instantaneous output power of a plurality of wind turbine generators;
and the optimizing sub-module is used for optimizing and solving the objective function by adopting a particle swarm algorithm based on constraint conditions according to the instantaneous output power of the wind turbines to obtain the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition.
The fuzzy controller construction module specifically comprises:
the variable determining submodule is used for determining the oscillation frequency as an input variable of the fuzzy controller, and the control parameter of the machine side converter is determined as an output variable of the fuzzy controller;
the domain acquisition sub-module is used for respectively acquiring a basic domain and a fuzzy domain of an input variable and a basic domain and a fuzzy domain of an output variable according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the fuzzy subset determining submodule is used for respectively determining that a fuzzy subset of input variables is { SS, S, ME, B and BB }, a fuzzy subset of machine side resistance remodeling control parameters is { LL, L, MM, M, H and HH }, and a fuzzy subset of machine side reactance remodeling control parameters is { Z, ZZ, L 'L', L ', M' M ', M', H 'H' }; wherein SS, S, ME, B, BB are respectively oscillation frequencies which are sequentially increased from small to large; LL, L, MM, M, H, HH are values of the machine side resistance remodeling control parameters which increase in sequence from small to large respectively; z, ZZ, L 'L', M 'M', H 'H' are values of machine side reactance remodeling control parameters which are sequentially increased from small to large respectively;
the membership function determining submodule is used for adopting a triangular membership function according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control conditionRespectively used as membership functions of an input variable and an output variable; wherein a and c are the values of two feet of a triangle in the triangle membership function curve, b is the value of a peak of the triangle in the triangle membership function curve, x is an input variable or an output variable, and mu is membership;
the change trend obtaining submodule is used for obtaining the change trend of the control parameters of the machine side converter along with the change of the oscillation frequency according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the fuzzy control rule making sub-module is used for making a fuzzy control rule between the oscillation frequency and the control parameter according to the change trend;
the fuzzy controller construction submodule is used for constructing the fuzzy controller based on the fuzzy control rule according to the basic argument and the fuzzy argument of the input variable, the basic argument and the fuzzy argument of the output variable, the fuzzy subset of the input variable, the fuzzy subset of the machine side resistance remodeling control parameter, the fuzzy subset of the machine side reactance remodeling control parameter, the membership function of the input variable and the membership function of the output variable.
The change trend of the control parameter of the machine side converter along with the change of the oscillation frequency is that the machine side resistance remodelling control parameter gradually decreases and then becomes stable along with the increase of the oscillation frequency, and the machine side reactance remodelling control parameter gradually increases and then becomes stable.
The fuzzy control rule between the oscillation frequency and the control parameter is as follows:
when the oscillation frequency is SS, the value of the machine side resistance remodeling control parameter is HH, and the value of the machine side reactance remodeling control parameter is Z;
when the oscillation frequency is S, the value of the machine side resistance remodeling control parameter is MM, and the value of the machine side reactance remodeling control parameter is M 'M';
when the oscillation frequency is ME, the value of the machine side resistance remodeling control parameter is LL, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is B, the value of the machine side resistance remodeling control parameter is L, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is BB, the value of the machine side resistance remodeling control parameter is M, and the value of the machine side reactance remodeling control parameter is H 'H'.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.

Claims (6)

1. A method for adaptive frequency subsynchronous oscillation suppression based on multi-branch impedance, the method comprising:
respectively carrying out simulation solution on the doubly-fed wind turbine generator system by adopting a particle swarm algorithm under different control conditions to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition; the control conditions comprise wind speed, grid strength and serial compensation; virtual impedance control is added to a machine side converter and a network side converter of the doubly-fed wind turbine generator system; the control parameters comprise a machine side resistance remodeling control parameter and a machine side reactance remodeling control parameter;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, formulating a fuzzy control rule between the oscillation frequency and the control parameters, and constructing a fuzzy controller based on the fuzzy control rule;
acquiring real-time oscillation frequency of a doubly-fed wind turbine generator system when subsynchronous oscillation occurs;
inputting the real-time oscillation frequency into a fuzzy controller based on the fuzzy control rule, and outputting real-time control parameters of a side converter;
the particle swarm algorithm is adopted to respectively carry out simulation solution on the doubly-fed wind turbine generator system under different control conditions to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, and the method specifically comprises the following steps:
constructing an objective function asThe constraint is Kr_ rsc>0 and Kx_ rsc>0; wherein sigma is the total overshoot of the oscillating power of the wind turbine generator relative to the steady-state value of the oscillating power, P (t) is the instantaneous output power of the wind turbine generator, and P N (V w ) To be in a specific state V w Steady-state output power, t, of corresponding wind turbine generator i For the start time, t i +T is the termination time, T is the time period, kr_ rsc is the machine side resistance remodeling control parameter, kx_ rsc is the machine side reactance remodeling control parameter;
simulating the doubly-fed wind turbine generator system under different control conditions to obtain instantaneous output power of a plurality of wind turbine generators;
according to the instantaneous output power of the wind turbines, based on constraint conditions, adopting a particle swarm algorithm to perform optimizing solution on an objective function, and obtaining control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the method comprises the steps of formulating a fuzzy control rule between the oscillation frequency and the control parameters according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, and constructing a fuzzy controller based on the fuzzy control rule, and specifically comprises the following steps:
determining the oscillation frequency as an input variable of the fuzzy controller, and determining a control parameter of the machine side converter as an output variable of the fuzzy controller;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, the basic domain and the fuzzy domain of the input variable and the basic domain and the fuzzy domain of the output variable are respectively obtained;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, respectively determining that a fuzzy subset of input variables is { SS, S, ME, B and BB }, a fuzzy subset of machine side resistance remodeling control parameters is { LL, L, MM, M, H and HH }, and a fuzzy subset of machine side reactance remodeling control parameters is { Z, ZZ, L 'L', L ', M' M ', M', H ', H' }; wherein SS, S, ME, B, BB are respectively oscillation frequencies which are sequentially increased from small to large; LL, L, MM, M, H, HH are values of the machine side resistance remodeling control parameters which increase in sequence from small to large respectively; z, ZZ, L 'L', M 'M', H 'H' are values of machine side reactance remodeling control parameters which are sequentially increased from small to large respectively;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, adopting a triangle membership functionRespectively used as membership functions of an input variable and an output variable; wherein a and c are the values of two feet of a triangle in the triangle membership function curve, b is the value of a peak of the triangle in the triangle membership function curve, x is an input variable or an output variable, and mu is membership;
according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition, the change trend of the control parameters of the machine side converter along with the change of the oscillation frequency is obtained;
according to the change trend, a fuzzy control rule between the oscillation frequency and the control parameter is formulated;
and constructing a fuzzy controller based on the fuzzy control rule according to the basic domain and the fuzzy domain of the input variable, the basic domain and the fuzzy domain of the output variable, the fuzzy subset of the input variable, the fuzzy subset of the machine side resistance remodeling control parameter, the fuzzy subset of the machine side reactance remodeling control parameter, the membership function of the input variable and the membership function of the output variable.
2. The adaptive frequency subsynchronous oscillation suppression method based on the multi-branch impedance according to claim 1, wherein the variation trend of the control parameter of the machine side converter along with the variation of the oscillation frequency is that the machine side resistance remodelling control parameter gradually decreases and then becomes stable along with the increase of the oscillation frequency, and the machine side reactance remodelling control parameter gradually increases and then becomes stable.
3. The adaptive frequency subsynchronous oscillation suppression method based on multi-branch impedance according to claim 1, wherein a fuzzy control rule between the oscillation frequency and a control parameter is:
when the oscillation frequency is SS, the value of the machine side resistance remodeling control parameter is HH, and the value of the machine side reactance remodeling control parameter is Z;
when the oscillation frequency is S, the value of the machine side resistance remodeling control parameter is MM, and the value of the machine side reactance remodeling control parameter is M 'M';
when the oscillation frequency is ME, the value of the machine side resistance remodeling control parameter is LL, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is B, the value of the machine side resistance remodeling control parameter is L, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is BB, the value of the machine side resistance remodeling control parameter is M, and the value of the machine side reactance remodeling control parameter is H 'H'.
4. An adaptive frequency subsynchronous oscillation suppression system based on multi-branch impedance, the system comprising:
the simulation module is used for respectively carrying out simulation solution on the doubly-fed wind turbine generator system by adopting a particle swarm algorithm under different control conditions to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition; the control conditions comprise wind speed, grid strength and serial compensation; virtual impedance control is added to a machine side converter and a network side converter of the doubly-fed wind turbine generator system; the control parameters comprise a machine side resistance remodeling control parameter and a machine side reactance remodeling control parameter;
the fuzzy controller construction module is used for formulating a fuzzy control rule between the oscillation frequency and the control parameter according to the control parameter of the machine side converter under the oscillation frequency corresponding to each control condition and constructing a fuzzy controller based on the fuzzy control rule;
the real-time oscillation frequency acquisition module is used for acquiring the real-time oscillation frequency of the doubly-fed wind turbine generator system when subsynchronous oscillation occurs;
the real-time control parameter output module is used for inputting the real-time oscillation frequency into the fuzzy controller based on the fuzzy control rule and outputting real-time control parameters of the side converter;
the simulation module specifically comprises:
an objective function construction submodule for constructing an objective function asThe constraint is Kr_ rsc>0 and Kx_ rsc>0; wherein sigma is the total overshoot of the oscillating power of the wind turbine generator relative to the steady-state value of the oscillating power, P (t) is the instantaneous output power of the wind turbine generator, and P N (V w ) To be in a specific state V w Steady-state output power, t, of corresponding wind turbine generator i For the start time, t i +T is the termination time, T is the time period, kr_ rsc is the machine side resistance remodeling control parameter, kx_ rsc is the machine side reactance remodeling control parameter;
the instantaneous output power obtaining submodule is used for simulating the doubly-fed wind turbine generator system under different control conditions to obtain instantaneous output power of a plurality of wind turbine generators;
the optimizing sub-module is used for optimizing and solving the objective function by adopting a particle swarm algorithm based on constraint conditions according to the instantaneous output power of the wind turbines to obtain control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the fuzzy controller construction module specifically comprises:
the variable determining submodule is used for determining the oscillation frequency as an input variable of the fuzzy controller, and the control parameter of the machine side converter is determined as an output variable of the fuzzy controller;
the domain acquisition sub-module is used for respectively acquiring a basic domain and a fuzzy domain of an input variable and a basic domain and a fuzzy domain of an output variable according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the fuzzy subset determining submodule is used for respectively determining that a fuzzy subset of input variables is { SS, S, ME, B and BB }, a fuzzy subset of machine side resistance remodeling control parameters is { LL, L, MM, M, H and HH }, and a fuzzy subset of machine side reactance remodeling control parameters is { Z, ZZ, L 'L', L ', M' M ', M', H 'H' }; wherein SS, S, ME, B, BB are respectively oscillation frequencies which are sequentially increased from small to large; LL, L, MM, M, H, HH are values of the machine side resistance remodeling control parameters which increase in sequence from small to large respectively; z, ZZ, L 'L', M 'M', H 'H' are values of machine side reactance remodeling control parameters which are sequentially increased from small to large respectively;
the membership function determining submodule is used for adopting a triangular membership function according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control conditionRespectively used as membership functions of an input variable and an output variable; wherein a and c are the values of two feet of a triangle in the triangle membership function curve, b is the value of a peak of the triangle in the triangle membership function curve, x is an input variable or an output variable, and mu is membership;
the change trend obtaining submodule is used for obtaining the change trend of the control parameters of the machine side converter along with the change of the oscillation frequency according to the control parameters of the machine side converter under the oscillation frequency corresponding to each control condition;
the fuzzy control rule making sub-module is used for making a fuzzy control rule between the oscillation frequency and the control parameter according to the change trend;
the fuzzy controller construction submodule is used for constructing the fuzzy controller based on the fuzzy control rule according to the basic argument and the fuzzy argument of the input variable, the basic argument and the fuzzy argument of the output variable, the fuzzy subset of the input variable, the fuzzy subset of the machine side resistance remodeling control parameter, the fuzzy subset of the machine side reactance remodeling control parameter, the membership function of the input variable and the membership function of the output variable.
5. The adaptive frequency subsynchronous oscillation suppression system based on multi-branch impedance of claim 4, wherein the variation trend of the control parameter of the machine side converter along with the variation of the oscillation frequency is that the machine side resistance remodelling control parameter gradually decreases and then becomes stable along with the increase of the oscillation frequency, and the machine side reactance remodelling control parameter gradually increases and then becomes stable.
6. The adaptive frequency subsynchronous oscillation suppression system based on multi-branch impedance of claim 4, wherein said fuzzy control rules between oscillation frequency and control parameters are:
when the oscillation frequency is SS, the value of the machine side resistance remodeling control parameter is HH, and the value of the machine side reactance remodeling control parameter is Z;
when the oscillation frequency is S, the value of the machine side resistance remodeling control parameter is MM, and the value of the machine side reactance remodeling control parameter is M 'M';
when the oscillation frequency is ME, the value of the machine side resistance remodeling control parameter is LL, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is B, the value of the machine side resistance remodeling control parameter is L, and the value of the machine side reactance remodeling control parameter is H';
when the oscillation frequency is BB, the value of the machine side resistance remodeling control parameter is M, and the value of the machine side reactance remodeling control parameter is H 'H'.
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