CN116345931A

CN116345931A - Inverter control mode and parameter identification method, system, equipment and medium

Info

Publication number: CN116345931A
Application number: CN202310362251.3A
Authority: CN
Inventors: 王彤; 王潇桐; 王增平
Original assignee: North China Electric Power University
Current assignee: North China Electric Power University
Priority date: 2023-04-07
Filing date: 2023-04-07
Publication date: 2023-06-27

Abstract

The invention discloses an inverter control mode and parameter identification method, an inverter control mode and parameter identification system, inverter control equipment and an inverter parameter identification medium, and relates to the technical field of inverter parameter identification. The method comprises the following steps: acquiring measurement data of the photovoltaic inverter in different control links; the control link comprises the following steps: a fault ride-through link, a fault ride-through recovery link, a current limiting link and a steady state control link; according to the measurement data, identifying control modes and parameters of the photovoltaic inverter in different control links to obtain an identification result; and the identification result is used for modeling and simulation analysis of the photovoltaic inverter so as to determine the operation characteristic of the photovoltaic inverter. According to the invention, the influence of different control modes on the parameter identification of the inverter and the characteristic analysis of the controller can be considered, the control modes and related parameters of different control links of the photovoltaic inverter can be effectively identified, and a model foundation is provided for modeling of the photovoltaic inverter and simulation analysis of a power system.

Description

Inverter control mode and parameter identification method, system, equipment and medium

Technical Field

The present invention relates to the technical field of inverter parameter identification, and in particular, to an inverter control mode and parameter identification method, system, device, and medium.

Background

In recent years, renewable energy sources typified by photovoltaic have been increasingly used in electric power systems. By the end of 2021, the Chinese photovoltaic power generation installation reaches 3.06 hundred million kilowatts, accounting for 13.8 percent of the total amount of the national power generation installation. At present, the photovoltaic power station mostly has the problems of lack of supporting capability, poor stability and the like of the system, and a series of challenges in the aspect of safety and stability are brought to a novel power system taking new energy as a main body. The photovoltaic inverter is one of core devices of a photovoltaic power generation system, and a clear inverter control model and parameters are the basis of photovoltaic power station modeling analysis and power system simulation analysis. And a plurality of control links of the photovoltaic inverter can adopt a plurality of control modes, and the control modes adopted by the inverters of different manufacturers and different models are different, so that great trouble is brought to modeling of the photovoltaic inverter and characteristic analysis of the photovoltaic inverter. Therefore, research on control modes and parameter identification methods of the photovoltaic inverter is needed, and compliance is provided for modeling and simulation of a new energy power system.

The existing photovoltaic inverter parameter identification method is mainly focused on identifying the control parameters of the photovoltaic inverter under the condition of known control modes, however, both the control modes and the control parameters of the inverter can directly influence the characteristics of the photovoltaic inverter. The existing photovoltaic inverter parameter identification method does not consider the influence of the control modes, and omits the important influence of different control modes on parameter identification and controller characteristic analysis.

Disclosure of Invention

The invention aims to provide a method, a system, equipment and a medium for identifying control modes and parameters of an inverter, which are used for effectively identifying the control modes and related parameters of different control links of a photovoltaic inverter by considering the influence of different control modes on the identification of the parameters of the inverter and the characteristic analysis of a controller, and providing a model foundation for modeling of the photovoltaic inverter and simulation analysis of an electric power system.

In order to achieve the above object, the present invention provides the following solutions:

an inverter control mode and parameter identification method comprises the following steps:

acquiring measurement data of the photovoltaic inverter in different control links; the control link comprises the following steps: a fault ride-through link, a fault ride-through recovery link, a current limiting link and a steady state control link; the measurement data of the fault crossing link comprises: active power, reactive power, active current, reactive current and terminal voltage; the measurement data of the fault ride-through recovery link comprises: a fault ride-through end time and an active current recovery curve; the measurement data of the current limiting link comprises: reactive current and total current; the measurement data of the steady-state control link comprises: the method comprises the steps of a station active power instruction, a station reactive power instruction, an inverter output active power, an inverter output reactive power, an inverter terminal voltage, a power factor reference value and a reactive power reference value;

According to the measurement data, identifying control modes and parameters of the photovoltaic inverter in different control links to obtain an identification result; the control mode of the fault crossing link comprises the following steps: no additional control, specified power control, specified current control and current control before crossing; the control mode of the fault ride-through recovery link comprises the following steps: no additional control, fixed slope control and control according to inertia constant; the control mode of the steady-state control link comprises the following steps: open loop control, PI control, and reactive/voltage coordination control; the parameters of the current limiting link include: an upper total current limit and an upper reactive current limit; and the identification result is used for modeling and simulation analysis of the photovoltaic inverter so as to determine the operation characteristic of the photovoltaic inverter.

Optionally, the identification result includes: the first identification result, the second identification result, the third identification result and the fourth identification result; according to the measurement data, identifying control modes and parameters of different control links to obtain an identification result, wherein the identification result comprises the following specific steps:

according to the measurement data of the fault crossing link, a control mode and parameters of the fault crossing link are identified by adopting a least square-based multiple linear regression, and a first identification result is obtained;

Identifying a control mode and parameters of the fault traversing recovery link according to the measurement data of the fault traversing recovery link to obtain a second identification result;

identifying parameters of the current limiting link according to the measurement data of the current limiting link to obtain a third identification result;

and identifying the control mode and the parameters of the steady-state control link by adopting a self-adaptive particle swarm algorithm according to the measurement data of the steady-state control link to obtain a fourth identification result.

An inverter control mode and parameter identification system, comprising:

the measurement data acquisition module is used for acquiring measurement data of the photovoltaic inverter in different control links; the control link comprises the following steps: a fault ride-through link, a fault ride-through recovery link, a current limiting link and a steady state control link; the measurement data of the fault crossing link comprises: active power, reactive power, active current, reactive current and terminal voltage; the measurement data of the fault ride-through recovery link comprises: a fault ride-through end time and an active current recovery curve; the measurement data of the current limiting link comprises: reactive current and total current; the measurement data of the steady-state control link comprises: the method comprises the steps of a station active power instruction, a station reactive power instruction, an inverter output active power, an inverter output reactive power, an inverter terminal voltage, a power factor reference value and a reactive power reference value;

The control mode and parameter identification module is used for identifying the control modes and parameters of the photovoltaic inverter in different control links according to the measurement data to obtain identification results; the control mode of the fault crossing link comprises the following steps: no additional control, specified power control, specified current control and current control before crossing; the control mode of the fault ride-through recovery link comprises the following steps: no additional control, fixed slope control and control according to inertia constant; the control mode of the steady-state control link comprises the following steps: open loop control, PI control, and reactive/voltage coordination control; the parameters of the current limiting link include: an upper total current limit and an upper reactive current limit; and the identification result is used for modeling and simulation analysis of the photovoltaic inverter so as to determine the operation characteristic of the photovoltaic inverter.

An electronic device includes a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to execute the above-described inverter control mode and parameter identification method.

A computer readable storage medium storing a computer program which when executed by a processor implements the above-described inverter control mode and parameter identification method.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects:

according to the method for identifying the control modes and the parameters of the inverter, provided by the invention, the measurement data of the photovoltaic inverter in different control links are obtained, the control modes and the parameters of the photovoltaic inverter in different control links are identified according to the measurement data, the identification result is obtained, the influence of the different control modes can be considered while the parameters of the inverter are identified, the mode which is adopted by the inverter is determined in a plurality of control modes, and finally the control modes and the parameters of the inverter fault crossing link, the fault crossing recovery link, the current limiting link and the steady-state control link are obtained, so that a model foundation can be provided for modeling and simulation analysis of the photovoltaic inverter and an electric power system, and data support is provided for operation characteristic analysis of the photovoltaic inverter and the electric power system.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and 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 an inverter control mode and parameter identification method provided by the invention;

fig. 2 is a block diagram of active power control of a photovoltaic inverter provided by the invention;

fig. 3 is a block diagram of reactive power control of a photovoltaic inverter provided by the invention;

FIG. 4 is a schematic diagram illustrating steady-state operation and voltage ride-through switching according to the present invention;

FIG. 5 is a flow chart of the low voltage ride through active control mode and parameter identification provided by the present invention;

FIG. 6 is a flow chart of the low voltage ride through reactive power control mode and parameter identification provided by the present invention;

FIG. 7 is a flowchart of a PSO algorithm including parameter boundary value adjustment according to the present invention;

FIG. 8 is a flowchart of steady-state active control link parameter identification provided by the present invention;

fig. 9 is a flowchart of steady-state reactive power control link parameter identification provided by the invention.

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.

Specifically, in the existing scheme, only control parameters of the photovoltaic inverter are identified, and different control modes existing in the control link of the photovoltaic inverter are not considered, namely, the data to be identified is obtained in a specific control mode by default, and for data obtained in other different control modes, accurate identification results are difficult to obtain, and because the control mode selection is not matched, the parameters obtained by identification of the photovoltaic inverter are likely to deviate greatly when the parameters are applied to modeling and simulation analysis of the photovoltaic inverter. The invention identifies the control mode adopted by the photovoltaic inverter while identifying the control parameters of the photovoltaic inverter, and realizes the integrated identification of the control mode and the control parameters. The integrated identification strategy of the control mode and the control parameter is provided for the fault ride-through link, the fault ride-through recovery link, the current limiting link and the steady-state control link, and the control mode and the parameter support of the photovoltaic inverter can be provided for modeling and simulation of the photovoltaic inverter and the power system.

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.

Example 1

The present embodiment provides a method for identifying control modes and parameters of an inverter, as shown in fig. 1, including:

step S1: acquiring measurement data of the photovoltaic inverter in different control links; the control link comprises the following steps: a fault ride-through link, a fault ride-through recovery link, a current limiting link and a steady state control link; the measurement data of the fault crossing link comprises: active power, reactive power, active current, reactive current and terminal voltage; the measurement data of the fault ride-through recovery link comprises: a fault ride-through end time and an active current recovery curve; the measurement data of the current limiting link comprises: reactive current and total current; the measurement data of the steady-state control link comprises: the method comprises the steps of a station active power instruction, a station reactive power instruction, an inverter output active power, an inverter output reactive power, an inverter terminal voltage, a power factor reference value and a reactive power reference value.

The measurement data of the different control links are determined based on an electromechanical transient model of the photovoltaic inverter. The electromechanical transient model of the photovoltaic inverter comprises: photovoltaic inverter steady-state control models, photovoltaic inverter voltage ride-through control (i.e., fault ride-through) models, and current limit models. The above models are described in detail below, respectively.

1) Photovoltaic inverter steady-state control model

The steady-state power control model of the photovoltaic inverter includes active and reactive control. The active control model is shown in fig. 2, and the control modes thereof include two modes of open loop control (p_flag=1) and PI control (p_flag=2).

(1) Open loop control: the required measurement value is the station power command Port and the inverter terminal voltage Vterm, the Port is delayed by T _pord Then obtaining the power reference value Pref, vterm with the passing time constant of T _rv The first-order inertia link of (2) is followed by obtaining a voltage calculated value, the power reference value is divided by the voltage calculated value to obtain a calculated current value, and the elapsed time constant is T _ip The active current instruction Ipcmd' is obtained after the first-order inertia link of (a).

(2) PI control: the required measurement value is a station power command Port, the actual output power Pe of the inverter, and the elapsed time constant of Pe is T _rp After the first-order inertia link of (2), comparing with Pref, inputting the difference value into PI control link, in which K _{p_lp} Is a proportionality coefficient, K _{i_lp} And outputting and obtaining an active current command Icmd' as an integral coefficient.

The reactive power control link of the inverter comprises reactive reference value selection and reactive current control mode selection, and the model structure and main control parameters of the reactive power control link are shown in figure 3.

The reactive power reference value selection includes three modes of constant power factor (qref_flag=0), fixed reactive power (qref_flag=1) and station reactive power instruction (qref_flag=2).

(1) Fixed power factor: and calculating a reactive reference value Qref according to the power factor reference value PFref and the filtered and delayed active power Pe_filt.

(2) And (3) determining reactive power: and setting the reactive power reference value Qref as the output reactive power Qe_ref of the inverter, and obtaining the reactive power reference value Qref by load flow calculation.

(3) Reactive power instruction of the station: station reactive power instruction Qord passing time constant is T _qord After the first-order inertia link of (2), a reactive reference value Qref is obtained.

Reactive power control modes include open loop control (q_flag=1), reactive/voltage coordination control (q_flag=2), reactive PI control (q_flag=3), and fixed reactive current control (q_flag=4).

(1) Open loop control:reactive power reference value Qref divided by vterm_filt (Vterm elapsed time constant T _rv The voltage calculated value is obtained after the first-order inertia link, and the passing time constant is T _iq The active current command Iqcmd' is obtained after the first-order inertia link of (a).

(2) Reactive/voltage coordination control: after comparing the voltage reference value with the voltage measurement value Vterm_filt, the voltage reference value is input into a PI link, wherein K _{p_lv} Is a proportionality coefficient, K _{i_lv} And outputting and obtaining a reactive current command Iqcmd' as an integral coefficient. The voltage reference value is the deviation between the power reference value Qref and the measurement value Qe_filt through the PI link (K) _{p_lqv} Is a proportionality coefficient, K _{i_lqv} An integral coefficient). Qe_filt is the output reactive power Qe of the inverter and the elapsed time constant is T _filt Is obtained after the first-order inertial link of the model (C).

(3) Reactive PI control: after comparing Qe_filt with Pref, the difference is input to the PI control link (where K _{p_lq} Is a proportionality coefficient, K _{i_lq} Integral coefficient), and outputting to obtain a reactive current command Iqcmd'.

(4) And (3) reactive current control: the reactive current command Iqcmd' is set to Iq0, i.e. the initial reactive current calculated from the power flow.

2) Photovoltaic inverter voltage ride through control model

When the voltage of the grid-connected point of the photovoltaic inverter drops to the low voltage crossing threshold V _Lin Below, or rise to, the high voltage ride through threshold V _Hin In the above-mentioned case, the inverter changes the control mode, and the current command source is converted from the steady-state operation control link (the output active current is Ipcmd ', the output reactive current is Iqcmd') to the voltage-ride-through operation control link (the output active current is Iphlvrt, and the output reactive current is Iqhlvrt). The model is shown in FIG. 4, in which the output current flows through a current limit model (upper and lower limits of active current Ipmax, iqmin, upper and lower limits of reactive current Iqmax, iqmin, upper limit of total current Imax) and an equivalent current transformer model (time constant T _g First-order inertial links) and then injected into the power grid.

The low voltage ride through active power control mode includes four control modes including steady state control (i.e. no additional control), specified power control, specified current control, and current control before ride through.

(1) Steady state control: the current command is not switched, and the active current and the reactive current are still in the normal running state. But now freezes the integration in the control link.

(2) Designating power control: designating active power P during low voltage ride through _LVRT Dividing the voltage by the voltage Vt of the machine end to obtain an active current instruction Ip _LVRT The calculation formula is as follows:

P _LVRT ＝K _P-LVRT *P ₀ +P _{set_LV}

Ip _LVRT ＝P _LVRT /Vt

wherein K is _{P_LVRT} For low pass active power coefficient, P _{set_LV} For low pass active power set point, P ₀ Is the initial active power.

(3) Specifying current control: designating active current command Ip during low voltage ride through _LVRT The calculation formula is as follows:

Ip _LVRT ＝K _1-Ip-LV *Vt+K _2-Ip-LV *Ip ₀ +Ip _{set_LV}

wherein K is _{1_Ip_LV} And K _{2_Ip_LV} All are low-pass active current calculation coefficients, ip _{set_LV} For low pass active current set point Ip ₀ Is the initial active current.

(4) Control according to current before crossing: maintaining the current before passing during the low voltage passing, the control mode can be regarded as (3) K in the designated current control _{1_Ip_LV} Taking 0, K _{2_Ip_LV} 1, ip is taken _{set_LV} Special case when 0 is taken:

Ip _LVRT ＝Ip ₀

the low voltage ride through reactive control includes three control modes, steady state control (i.e., no additional control), specified power, specified current.

(1) Steady state control: and the current command is a reactive current command after freezing the integration link in a normal running state.

(2) Designating power control: designating reactive power Q during low voltage ride through _LVRT Dividing by the terminal voltage Vt to obtain nothingPower current command Iq _LVRT The calculation formula is as follows:

Q _LVRT ＝K _Q-LVRT *Q ₀ +Q _{set_LV}

Iq _LVRT ＝Q _LVRT /Vt

wherein K is _{Q_LVRT} For low through reactive power coefficient, Q _{set_LV} For low penetration reactive power set point, Q ₀ Is the initial reactive power.

(3) Specifying current control: introducing a low voltage ride-through threshold V _Lin At this time, the current command is:

Iq _LVRT ＝K _1-Iq-LV *(V _Lin -Vt)+K _2-Iq-LV *Iq ₀ +Iq _{set_LV}

wherein K is _{1_Iq_LV} And K _{2_Iq_LV} All are low-pass reactive current calculation coefficients, iq _{set_LV} Is a low pass reactive current set value, iq ₀ Is the initial reactive current.

The active and reactive control modes of the high voltage ride through are the same as those of the low voltage ride through, wherein, the designated current control part in the high voltage ride through reactive control mode has the following reactive current instruction:

Iq _HVRT ＝K _1-Iq-HV *(V _Hin -Vt)+K _2-Iq-HV *Iq ₀ +Iq _{set_HV}

wherein K is _{1_Iq_HV} And K _{2_Iq_HV} All are high-pass reactive current calculation coefficients, V _Hin For high voltage crossing threshold, iq _{set_HV} For the high-pass reactive current set value Iq ₀ Is the initial reactive current.

3) Current limiting model

In order to avoid overcurrent of the photovoltaic inverter, the output current of the steady-state operation and the voltage crossing links are input into a current limiting link, the active single current, the reactive current and the total current which exceed the limit values are limited, the active current output is preferentially ensured in normal operation, the reactive current output is preferentially ensured in voltage crossing, and the important parameters of the current limiting link comprise the upper limit I of the total current _max And the upper limit Iq of reactive current _max In the case where current limitation is considered, the current limitation,the active current during voltage ride through is:

Iqcmd＝min(Iq _max ,Iqhlvrt)

where Iq is reactive current output by the photovoltaic inverter, and Iphlvrt, iqhlvrt is an output value of the voltage crossing link in fig. 4.

Step S2: according to the measurement data, identifying control modes and parameters of the photovoltaic inverter in different control links to obtain an identification result; the control mode of the fault crossing link comprises the following steps: no additional control, specified power control, specified current control and current control before crossing; the control mode of the fault ride-through recovery link comprises the following steps: no additional control, fixed slope control and control according to inertia constant; the control mode of the steady-state control link comprises the following steps: open loop control, PI control, and reactive/voltage coordination control; the parameters of the current limiting link include: an upper total current limit and an upper reactive current limit; and the identification result is used for modeling and simulation analysis of the photovoltaic inverter so as to determine the operation characteristic of the photovoltaic inverter.

Further, the identification result includes: the first identification result, the second identification result, the third identification result and the fourth identification result; the step S2 specifically comprises the following steps:

Step S21: and identifying the control mode and parameters of the fault crossing link by adopting the multiple linear regression based on least square according to the measurement data of the fault crossing link to obtain a first identification result.

The step S21 specifically includes:

step S211: determining an available data set according to the measured data of the fault crossing link and the parameters of the current limiting link; the available data set is obtained by removing current limiting data from the measurement data of the fault crossing link.

Step S212: and identifying parameters in a specified power control mode by adopting a least square-based multiple linear regression according to the available data set and a specified power calculation formula, and determining a difference value between a power calculation value and a power measurement value according to the parameters in the specified power control mode as a first difference value.

Step S213: and identifying parameters in a specified current control mode by adopting a least square-based multiple linear regression according to the available data set and a specified current calculation formula, and determining a difference value between a current calculation value and a current measurement value according to the parameters in the specified current control mode as a second difference value.

Step S214: and judging whether the first difference value and the second difference value are both larger than a set error threshold value or not to obtain a first judgment result.

Step S215: and if the first judging result is yes, determining that the control mode in the first identification result is no additional control.

Step S216: and if the first judgment result is negative, judging whether the first difference value is smaller than the second difference value, and obtaining a second judgment result.

Step S217: if the second judgment result is yes, determining that the control mode in the first identification result is the appointed power control, and the parameter in the first identification result is the parameter in the appointed power control mode.

Step S218: if the second judgment result is negative, determining that the control mode in the first identification result is the appointed current control or the current control before crossing, and the parameter in the first identification result is the parameter in the appointed current control mode or the parameter in the current control mode before crossing.

Wherein, the fault crossing link includes: the system comprises a fault ride-through active control link and a fault ride-through reactive control link.

When in the fault ride-through reactive control link: if the second judgment result is negative, determining that the control mode of the first identification result is the appointed current control, and the parameter of the first identification result is the parameter in the appointed current control mode.

When in the fault ride-through reactive control link: if the second judgment result is negative, judging whether the parameters in the appointed current control mode meet the set conditions or not, and obtaining a third judgment result; the parameters in the specified current control mode include: the first fault ride-through current calculation coefficient, the second fault ride-through current calculation coefficient and the fault ride-through current set point; the setting conditions are as follows: the difference value between the first fault crossing current calculation coefficient and 0 is smaller than a first set value, the difference value between the second fault crossing current calculation coefficient and 1 is smaller than a second set value, and the difference value between the fault crossing current set value and 0 is smaller than a third set value; if the third judgment result is yes, determining that the control mode in the first identification result is the current control before crossing, and the parameter in the first identification result is the parameter in the current control mode before crossing; if the third judging result is negative, determining that the control mode in the first identifying result is the appointed current control, and the parameter in the first identifying result is the parameter in the appointed current control mode. In one embodiment, the first set value, the second set value and the third set value are all set to 1e-5.

The method comprises the following steps of:

assuming z is the same as x ₁ ,x ₂ ,…x _n There is a linear relationship between them, then a linear equation is obtained:

z＝b ₀ +b ₁ x ₁ +b ₂ x ₂ +…+b _n x _n

for k sets of input data:

Z＝[ _z (1)z(2)···z(k)] ^T

θ＝[b ₀ b ₁ …b _n ] ^T

the above is rewritable in matrix form:

Z＝Xθ

setting parameter estimation values as follows:

the estimated output is +.>

The sum of squares of the differences between the measured and estimated values can be expressed as:

when (when)

When the minimum is taken, the estimated value of the parameter is considered +.>

Closest to the true value θ, there are, according to the extremum theorem:

and (3) solving after finishing to obtain:

the above identification method is discussed in detail below with reference to a control mode of voltage ride through of the photovoltaic inverter, taking a low voltage ride through active control mode as an example. The parameters to be identified are shown in table 1.

TABLE 1 Low Voltage ride through active standby identification control modes and parameter summary tables

Since there are multiple control modes and parameters, the least square based multiple linear regression is adopted to identify the control parameters, and meanwhile, the identification errors of different control modes are calculated, so that the mode and the set parameters adopted by the model are determined, and the identification strategy is shown in fig. 5.

(1) Data input: test data of 0.05-0.8p.u. different voltage drops and different initial active powers.

(2) And (3) data processing: read rated capacity S _n Sampling interval T _s Entering a low voltage ride through threshold V _Lin 。

(3) And obtaining active current, machine end voltage and active power steady state values before and during low pass, identifying current limiting link parameters, and confirming available data sets.

(4) According to a specified power calculation formula, performing multiple linear regression by a least square method, and identifying to obtain K _{p_LVRT} 、P _{set_LV} Calculating a power calculation value P according to a specified power control mode by using the parameters obtained by identification _cal Calculate the power measurement value P _mea E1 of the difference e1 of (c).

Wherein P is ₀ i, i=1, 2, …, n is the active power before the i-th group data enters the low voltage ride through.

(5) According to a specified current calculation formula, K is obtained by identification by adopting the same method _{1_Ip_LV} 、K _{2_Ip_LV} 、Ip _{set_LV} Calculating a current calculation value I according to a specified current control mode by using the parameters obtained by identification _cal Calculate the current measurement value I _mea E2 of the difference e2 of (c).

Wherein V is _t i,i＝1,2,… n is the terminal voltage, ip during the low voltage ride through period of the ith group of data ₀ i, i=1, 2, …, n is the active current before the i-th group data enters the low voltage ride through.

(6) If e1>0.1 and e2>0.1, both control modes are considered to be inapplicable, and the control mode is judged to be no additional control (when simulation data is adopted, the error threshold can be selected to be 1 e-5).

(7) If e1<0.1 and e1<0.1 are satisfied, the parameter set with small error value is considered to be the control mode and the corresponding parameter.

(8) If the specified current control is judged in the step (7), judging whether the current value is an active current before passing through or not, if the current value is K _{1_Ip_LV} ≈0、K _{2_Ip_LV} ≈1、Ip _{set_LV} And (4) the control mode is current control before crossing, and if the conditions are not met, the control mode is conventional specified current control.

The reactive power control mode and the parameter identification method are similar to the active power, and are different from the identification process according to the current control mode before crossing in the step (8), wherein the identification flow is shown in fig. 6, and the high voltage crossing active power, the reactive power control mode and the parameter identification method are the same as the low voltage crossing identification method, so that the details are not repeated here.

Step S22: and identifying the control mode and parameters of the fault crossing recovery link according to the measurement data of the fault crossing recovery link to obtain a second identification result. The voltage crossing recovery control mode (namely the fault crossing recovery control mode) comprises no additional control, fixed slope and inertia constant. Reactive current recovery is generally chosen without additional control and will not be described in detail here.

The step S22 specifically includes:

Step S221: and taking the fault ride-through ending moment as a starting point, determining all data points in a range from a first setting moment to a second setting moment on the active current recovery curve as a target data set, and connecting the data points at the first setting moment and the second setting moment on the active current recovery curve to obtain a target straight line.

Step S222: data error absolute values of data points in the target data set and corresponding data points on the target line are calculated.

Step S223: for any one target data set, if the absolute value of the data error of more than 95% of the data points is less than or equal to 10% of the corresponding data points on the target straight line, determining that the target data set meets the fixed slope recovery.

Step S224: and judging whether more than 90% of target data sets meet the fixed slope recovery or not, and obtaining a fourth judgment result.

Step S225: and if the fourth judgment result is yes, determining the control mode in the second identification result as fixed slope control, and determining the parameters in the second identification result as the average value of the slopes of the target straight lines corresponding to all the target data sets meeting fixed slope recovery.

Step S226: and if the fourth judgment result is negative, fitting the data points in the target data set by using a polynomial fitting based on least squares to obtain a fitting polynomial corresponding to the target data set.

Step S227: and calculating an inertia time constant of the data points in the target data set according to the fitting polynomial.

Step S228: for any one target data set, if more than 95% of the inertia time constants are distributed within +/-10% of the average value of the inertia time constants, determining that the target time constant corresponding to the target data set is the average value of the inertia time constants of all data points in the target data set.

Step S229: and judging whether the difference value between the maximum value and the minimum value in all the target time constants is smaller than or equal to 10% of the average value of all the target time constants, and obtaining a fifth judgment result.

Step S2210: and if the fifth judging result is yes, determining that the control mode in the second identifying result is controlled according to the inertia constant, and determining that the parameters in the second identifying result are average values of all target time constants.

Step S2211: and if the fifth judging result is negative, determining that the control mode in the second identifying result is no additional control.

As a specific embodiment, the active current recovery control mode and the parameter identification strategy are as follows:

(1) Using the fault crossing ending time as a starting point, connecting two data points of 20ms and 120ms after the fault is ended on the active current recovery curve by using a straight line L to obtain the slope d of the straight line L _L 。

(2) Calculating corresponding moment value Ip on each data point Ip (i) and straight line L within 20ms to 120ms after the fault is ended _L (i) An absolute value of error delta (i).

(3) If more than 95% of the absolute value delta (i) of the data errors are not more than 10% of the corresponding data points Ip (i), the group of data is judged to meet the fixed slope recovery.

(4) For all n groups of data, if 90% or more of the data groups satisfy the fixed slope recovery, it is determined that the failure recovery control mode at this time is the fixed slope control, and the fixed slope parameter is d of each data group satisfying the fixed slope recovery _L Average value.

(5) And if the constant slope control is not satisfied, adopting a polynomial fitting based on least squares to obtain a smooth curve, and fitting data in a time of 20ms to 120ms after the fault is ended to obtain a 5-order polynomial.

(6) And calculating the inertia time constant T of each data point by discretized data in the 5 th order polynomial. If 95% of T is distributed within + -10% of the average, the target time constant for the set of data can be determined to be the average T of T _mean 。

(7) If all target time constants T _mean If the difference between the maximum and minimum values of (a) is not more than 10% of the average value, determining that the control mode at that time is to control according to an inertia curve (i.e. control according to inertia constants), wherein the inertia time constants are each set of target time constants T _mean And otherwise, determining that no additional control exists.

Step S23: and identifying parameters of the current limiting link according to the measurement data of the current limiting link to obtain a third identification result.

The step S23 specifically includes:

step S231: and converting the measurement data of the current limiting link into per unit value to obtain a test data set.

Step S232: judging whether the test data set has a group with the maximum reactive current larger than 1.05p.u. or not, and obtaining a sixth judging result.

Step S233: and if the sixth judgment result is yes, determining all groups with maximum reactive current within the range of 0.01p.u. of the maximum reactive current and the maximum value of the maximum reactive current as the first current limiting groups, and determining the upper limit of the reactive current in the third identification result as the average value of the maximum reactive current of all the first current limiting groups.

Step S234: and if the sixth judgment result is negative, determining the upper limit of the reactive current in the third identification result to be 1.1p.u.

Step S235: judging whether the test data set has a group with the maximum total current greater than 1.1p.u. or not, and obtaining a seventh judgment result.

Step S236: if the seventh judgment result is yes, all groups with the maximum total current within the range of 0.01p.u. of the maximum total current and the maximum value of the maximum total current are determined as second current limiting groups, and the upper limit of the total current in the third identification result is determined as the average value of the maximum total currents of all the second current limiting groups.

Step S237: and if the seventh judgment result is negative, determining the upper limit of the total current in the third identification result as 1.2p.u..

As a specific implementation manner, based on the current limiting model, considering typical parameters of the current limiting link, the current limiting link parameters are identified by adopting the following method:

(1) Inputting test data of 0.8-1 power factor and 0.05-0.8p.u. voltage drop.

(2) If the maximum reactive current value exceeds the group of 1.05p.u., the maximum value and the group within the range of 0.01p.u. are judged to be limited, the partial data set is removed in further parameter identification, and the current limiting value is the data set average value. Otherwise, judge Iq _max ＝1.1。

(3) If the maximum total current value exceeds the group of 1.1p.u., the maximum value and the group within the range of 0.01p.u. are judged to be limited, the partial data set is removed in further parameter identification, and the limiting value is the data set mean value. Otherwise, judge I _max ＝1.2。

Step S24: and identifying the control mode and the parameters of the steady-state control link by adopting a self-adaptive particle swarm algorithm according to the measurement data of the steady-state control link to obtain a fourth identification result.

The step S24 specifically includes:

step S241: and dividing the measurement data of the steady-state control link into a calculation data set and a verification data set according to a set proportion.

Step S242: and identifying parameters under each control mode of the steady-state control link by adopting a self-adaptive particle swarm algorithm according to the calculation data set. Wherein, for any control mode, when the parameter is identified by adopting the self-adaptive particle swarm algorithm: firstly, identifying all parameters under the control mode by adopting a self-adaptive particle swarm algorithm; secondly, selecting a plurality of calculation data sets with smaller fitness value of the objective function to respectively calculate the average value of each parameter, and determining the value of the control link parameter in the calculation data sets; then, identifying a measured value time constant under the control mode by adopting a self-adaptive particle swarm algorithm; and finally, selecting a plurality of calculation data sets with smaller fitness value of the objective function to calculate the average value of each measured value time constant, and determining the value of each measured value time constant. The parameters in each control mode of the steady-state control link comprise control link parameters and measured value time constants.

Step S243: and calculating error values in each control mode according to the verification data set and the parameters in each control mode.

Step S244: comparing the error values in the control modes, determining the control mode in the fourth identification result as the control mode with the minimum error value, and determining the parameter in the fourth identification result as the parameter in the control mode with the minimum error value.

Compared with the voltage crossing control link which adopts a steady state value identification control mode and parameters, the steady state control link under the normal operation condition has more control modes and parameters, and the dynamic process of the inverter is required to be utilized for identification, and a group of parameters with the minimum deviation between the response curve and the curve to be identified is found in the control modes and parameters, so that a particle swarm algorithm is used as an optimizing tool.

Particle swarm optimization has been derived as a basic intelligent optimization algorithm with many improvements, such as changing inertial and learning factors, changing speed dimensions, optimizing mutation strategies, etc. The invention adds a feedback link for adjusting the optimizing range of the parameter on the basis of the self-adaptive particle swarm algorithm, namely when the parameter in the optimal solution comprises a boundary value, the boundary value of the parameter is enlarged, and the solution is carried out again, so that the equipment for atypical parameters is ensured, and the optimal solution of the atypical parameter under different control models can still be found by the identification strategy provided by the invention. For the case that the parameter x is greater than 0, the method for adjusting the parameter boundary value is as follows:

Wherein x is _maxi 、x _mini Respectively the upper limit and the lower limit of the optimizing range of the original parameter x, x _best For PSO optimizing result, x _maxi+1 、x _mini+1 And (5) respectively searching the upper limit and the lower limit of the optimizing range of the updated parameter x. In the particle swarm algorithm adopted by the invention, as shown in fig. 7, each particle contains all parameters to be identified, the position of the particle is changed, namely, the parameter value is changed, the particle speed is changed, namely, the parameter value is changed, the optimal solution is the optimal group of parameters obtained by identification, namely, the particle motion is in a high-dimensional space formed by the parameters to be identified, and the main flow of the identification method is the same as that of the conventional particle swarm algorithm.

The following discusses in detail the parameter identification of the steady-state active control mode and the steady-state reactive control mode, respectively.

1) Steady state active control mode and parameter identification

The steady-state active control model of the photovoltaic inverter is shown in fig. 2 and comprises the same as that in fig. 4An active converter link ", wherein T _pord The delay time of the station command, i.e. the time interval between the command change time and the active current change time, can be identified by changing the control command. The control link adopts two modes of open loop control and PI control, and parameters to be identified are shown in Table 2.

TABLE 2 active control links to-be-identified control modes and parameter summary tables

The active control mode and parameters are identified by adopting a self-adaptive particle swarm algorithm, a plurality of groups of data are used for identifying a plurality of parameters of the two control modes at the same time, the parameters of a control link are preferentially identified, and then the measured value time constant is identified, wherein the identification process is shown in fig. 8 and comprises the following steps.

(1) In order to effectively identify different control modes, more than 3 groups of simulation or actual measurement data need to be acquired.

(2) 3 groups of data are sequentially input to the two control models, all parameters are identified by adopting the PSO algorithm provided by the invention, and for each control mode, the fitness value (the deviation between the identification result and the input data) of the objective function of the 3 groups of data is obtained.

(3) Selecting two sets of parameter identification results with smaller target fitness function values in 3 sets of data, averaging, and then confirming K _p 、K _i 、T _ip Parameters.

(4) Further identify T _rp 、T _g 、T _rv For each control mode, obtaining the fitness value of the objective function of 3 groups of data, selecting two smaller groups of parameter identification results, averaging and then confirming T _rp 、T _g 、T _rv Parameters.

(5) After obtaining the respective parameters of the two control modes, verifying the two control modes by using the rest data sets, comparing waveform errors of the two control modes, and determining the control mode set by the inverter as the control mode with smaller confirmed errors, and determining the parameter value according to the identification results of the steps (3) and (4).

In this embodiment, as shown in steps (2) - (4), when determining parameters in a control mode, two times of PSO algorithm are respectively adopted for identification, where the first identified parameter is a key parameter, the parameter sensitivity is high, and the second identified parameter is a non-key parameter, the parameter sensitivity is low, and by prioritizing the parameters with high identification sensitivity, the accuracy of the identification result can be improved. In this embodiment, the active control link control mode and the parameter identification result are shown in table 3.

TABLE 3 active control link control mode and parameter identification results

Parameter name	Setting value	Adaptive PSO	Error of	Standard PSO	Error of
						Control mode	PI control	PI control	/	PI control	/
K _{p_lp}	0.2	0.2002	0.1％	0.2011	0.55％
						K _{i_lp}	3.5	3.5000	0	3.5034	0.97％
T _rp	0.01	0.0098	2％	0.0073	27％
						T _g	0.01	0.0101	1％	0.0132	32％

2) Reactive control mode and parameter identification for steady-state operation

The photovoltaic inverter reactive power control model is shown in fig. 3 and comprises an equivalent converter link in fig. 4, wherein T _qord The delay time of the station command, i.e. the time interval between the command change time and the active current change time, can be identified by changing the control command. The reactive power control link of the converter comprises reactive power reference value selection, reactive power current control mode selection and reactive power/voltage coordination control mode selection, and parameters to be identified are shown in table 4.

TABLE 4 reactive control link to-be-identified control mode and parameter summary table

The overall identification flow of the reactive power control link is shown in fig. 9, and comprises the following steps.

(2) And 3 groups of data are sequentially input to the three control models, all parameters are identified by adopting the PSO algorithm provided by the invention, and for each control mode, the fitness value (the deviation between the identification result and the input data) of the objective function of the 3 groups of data is obtained.

(3) Selecting two sets of parameter identification results with smaller target fitness function values in 3 sets of data, averaging, and then confirming each proportional integral parameter and T _iq 。

(4) Further identify T _fltr 、T _g 、T _rv For each control mode, obtaining the fitness value of the objective function of 3 groups of data, selecting two smaller groups of parameter identification results, averaging and then confirming T _fltr 、T _g 、T _rv Parameters.

(5) After obtaining the respective parameters of the three control modes, verifying the three control modes by using the rest data sets, comparing waveform errors of the three control modes, and determining the control mode set by the inverter as the control mode with smaller confirmed errors, and determining the parameter value according to the identification results of the steps (3) and (4).

Example two

In order to execute a corresponding method of the above embodiment to achieve the corresponding functions and technical effects, an inverter control mode and parameter identification system is provided below, including: a measurement data acquisition module, a control mode and a parameter identification module. The measurement data acquisition module is used for acquiring measurement data of the photovoltaic inverter in different control links; the control mode and parameter identification module is used for identifying the control modes and parameters of the photovoltaic inverter in different control links according to the measurement data to obtain identification results; and the identification result is used for modeling and simulation analysis of the photovoltaic inverter so as to determine the operation characteristic of the photovoltaic inverter.

The control link comprises the following steps: a fault ride-through link, a fault ride-through recovery link, a current limiting link and a steady state control link; the measurement data of the fault crossing link comprises: active power, reactive power, active current, reactive current and terminal voltage; the measurement data of the fault ride-through recovery link comprises: a fault ride-through end time and an active current recovery curve; the measurement data of the current limiting link comprises: reactive current and total current; the measurement data of the steady-state control link comprises: the method comprises the steps of a station active power instruction, a station reactive power instruction, an inverter output active power, an inverter output reactive power, an inverter terminal voltage, a power factor reference value and a reactive power reference value. The control mode of the fault crossing link comprises the following steps: no additional control, specified power control, specified current control and current control before crossing; the control mode of the fault ride-through recovery link comprises the following steps: no additional control, fixed slope control and control according to inertia constant; the control mode of the steady-state control link comprises the following steps: open loop control, PI control, and reactive/voltage coordination control; the parameters of the current limiting link include: an upper total current limit and an upper reactive current limit.

Example III

The embodiment of the invention also provides an electronic device, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor is used for running the computer program to enable the electronic device to execute the identification method of the inverter control mode and the parameters in the first embodiment. The electronic device may be a server.

In addition, the present invention also provides a computer readable storage medium storing a computer program which when executed by a processor implements the method for identifying the inverter control mode and the parameters in the first embodiment.

In summary, the invention provides a method, a system, a device and a medium for identifying control modes and parameters of an inverter, which aim at the problems in the prior art, firstly determine main control modes and important parameters of different links such as a steady-state operation link, a fault crossing link and the like, further identify the control modes and parameters of the fault crossing link by using the measurement values of power, voltage, current and the like, identify the control modes and parameters of the steady-state control link by using a multiple linear regression based on least square, identify the parameters of the inverter by using an adaptive particle swarm algorithm, consider the influence of the different control modes while identifying the parameters of the inverter, determine the modes adopted by the inverter in multiple control modes, and finally obtain the models and parameters of the steady-state control and the voltage crossing link of the inverter.

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

1. An inverter control mode and parameter identification method is characterized by comprising the following steps:

2. The method for identifying the inverter control mode and the parameters according to claim 1, wherein the identification result includes: the first identification result, the second identification result, the third identification result and the fourth identification result; according to the measurement data, identifying control modes and parameters of different control links to obtain an identification result, wherein the identification result comprises the following specific steps:

3. The method for identifying the control mode and the parameters of the inverter according to claim 2, wherein the method for identifying the control mode and the parameters of the fault-ride-through link by using least-squares-based multiple linear regression according to the measurement data of the fault-ride-through link, comprises the following steps:

determining an available data set according to the measured data of the fault crossing link and the parameters of the current limiting link; the available data set is obtained by removing current limiting data from the measurement data of the fault crossing link;

identifying parameters in a specified power control mode by adopting a least square-based multiple linear regression according to the available data set and a specified power calculation formula, and determining a difference value between a power calculation value and a power measurement value according to the parameters in the specified power control mode as a first difference value;

Identifying parameters in a specified current control mode by adopting a least square-based multiple linear regression according to the available data set and a specified current calculation formula, and determining a difference value between a current calculation value and a current measurement value according to the parameters in the specified current control mode as a second difference value;

judging whether the first difference value and the second difference value are both larger than a set error threshold value or not to obtain a first judgment result;

if the first judgment result is yes, determining that the control mode in the first identification result is no additional control;

if the first judgment result is negative, judging whether the first difference value is smaller than the second difference value, and obtaining a second judgment result;

if the second judgment result is yes, determining that the control mode in the first identification result is the appointed power control, and the parameter in the first identification result is the parameter in the appointed power control mode;

if the second judgment result is negative, determining that the control mode in the first identification result is the appointed current control or the current control before crossing, and the parameter in the first identification result is the parameter in the appointed current control mode or the parameter in the current control mode before crossing.

4. The method for identifying the inverter control mode and the parameters according to claim 3, wherein the fault-ride-through procedure comprises: a fault ride-through active control link and a fault ride-through reactive control link;

when in the fault ride-through reactive control link: if the second judgment result is negative, determining that the control mode of the first identification result is the appointed current control, and the parameter of the first identification result is the parameter in the appointed current control mode;

when in the fault ride-through reactive control link: if the second judgment result is negative, judging whether the parameters in the appointed current control mode meet the set conditions or not, and obtaining a third judgment result; the parameters in the specified current control mode include: the first fault ride-through current calculation coefficient, the second fault ride-through current calculation coefficient and the fault ride-through current set point; the setting conditions are as follows: the difference value between the first fault crossing current calculation coefficient and 0 is smaller than a first set value, the difference value between the second fault crossing current calculation coefficient and 1 is smaller than a second set value, and the difference value between the fault crossing current set value and 0 is smaller than a third set value; if the third judgment result is yes, determining that the control mode in the first identification result is the current control before crossing, and the parameter in the first identification result is the parameter in the current control mode before crossing; if the third judging result is negative, determining that the control mode in the first identifying result is the appointed current control, and the parameter in the first identifying result is the parameter in the appointed current control mode.

5. The method for identifying the control mode and the parameters of the inverter according to claim 2, wherein the identifying the control mode and the parameters of the fault ride-through recovery link according to the measurement data of the fault ride-through recovery link to obtain the second identification result specifically comprises:

determining all data points in a range from a first set time to a second set time on the active current recovery curve as a target data set by taking the fault ride-through ending time as a starting point, and connecting the data points at the first set time and the second set time on the active current recovery curve to obtain a target straight line;

calculating the absolute value of the data error between the data point in the target data group and the corresponding data point on the target straight line;

for any one target data set, if the absolute value of the data error of more than 95% of data points is less than or equal to 10% of the corresponding data points on the target straight line, determining that the target data set meets the fixed slope recovery;

judging whether more than 90% of target data sets meet fixed slope recovery or not, and obtaining a fourth judgment result;

if the fourth judgment result is yes, determining a control mode in the second identification result as fixed slope control, and determining parameters in the second identification result as average values of slopes of the target straight lines corresponding to all target data sets meeting fixed slope recovery;

If the fourth judgment result is negative, fitting the data points in the target data set by using a polynomial fitting based on least squares to obtain a fitting polynomial corresponding to the target data set;

calculating an inertial time constant of a data point in the target data set according to the fitting polynomial;

for any one target data set, if more than 95% of inertia time constants are distributed within +/-10% of the average value of the inertia time constants, determining that the target time constant corresponding to the target data set is the average value of the inertia time constants of all data points in the target data set;

judging whether the difference value between the maximum value and the minimum value in all the target time constants is smaller than or equal to 10% of the average value of all the target time constants, and obtaining a fifth judgment result;

if the fifth judgment result is yes, determining that the control mode in the second identification result is controlled according to the inertia constant, and determining that the parameters in the second identification result are average values of all target time constants;

and if the fifth judging result is negative, determining that the control mode in the second identifying result is no additional control.

6. The method for identifying the inverter control mode and the parameters according to claim 2, wherein the step of identifying the parameters of the current limiting link according to the measurement data of the current limiting link to obtain a third identification result comprises:

Converting the measurement data of the current limiting link into per unit value to obtain a test data set;

judging whether a group with the maximum reactive current greater than 1.05p.u. exists in the test data group, and obtaining a sixth judgment result;

if the sixth judgment result is yes, determining all groups with maximum reactive current within the range of 0.01p.u. of the maximum reactive current and the maximum value of the maximum reactive current as first current limiting groups, and determining the upper limit of the reactive current in the third identification result as the average value of the maximum reactive current of all the first current limiting groups;

if the sixth judgment result is negative, determining the upper limit of the reactive current in the third identification result to be 1.1p.u.;

judging whether a group with the maximum total current greater than 1.1p.u. exists in the test data group or not, and obtaining a seventh judgment result;

if the seventh judgment result is yes, determining all groups with the maximum total current within the range of 0.01p.u. of the maximum total current and the maximum value of the maximum total current as second current limiting groups, and determining the upper limit of the total current in the third identification result as the average value of the maximum total current of all the second current limiting groups;

And if the seventh judgment result is negative, determining the upper limit of the total current in the third identification result as 1.2p.u..

7. The method for identifying the control mode and the parameters of the inverter according to claim 2, wherein the method for identifying the control mode and the parameters of the steady-state control link by using the adaptive particle swarm algorithm according to the measurement data of the steady-state control link to obtain a fourth identification result comprises the following steps:

dividing the measurement data of the steady-state control link into a calculation data set and a verification data set according to a set proportion;

identifying parameters under each control mode of a steady-state control link by adopting a self-adaptive particle swarm algorithm according to the calculation data set;

calculating error values in each control mode according to the verification data set and parameters in each control mode;

comparing the error values in the control modes, determining the control mode in the fourth identification result as the control mode with the minimum error value, and determining the parameter in the fourth identification result as the parameter in the control mode with the minimum error value.

8. An inverter control mode and parameter identification system, comprising:

9. An electronic device comprising a memory and a processor, the memory storing a computer program, the processor running the computer program to cause the electronic device to perform the method of identifying the inverter control mode and parameters according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that it stores a computer program which, when executed by a processor, implements the inverter control mode and parameter identification method according to any one of claims 1 to 7.