Method and device for determining control parameters of photovoltaic power generation system

Abstract

The invention provides a method and device for determining control parameters of a photovoltaic power generation system, the photovoltaic power generation system is provided with an inverter, and the method comprises the steps: obtaining a plurality of to-be-determined control parameters of the inverter; under the condition that a preset condition is met, the absolute sensitivities of the multiple to-be-determined control parameters are calculated respectively, the preset condition is that different observation variables of the inverter are disturbed, and the multiple to-be-determined control parameters have the corresponding absolute sensitivities under the condition of disturbance each time; according to the absolute sensitivity corresponding to the multiple to-be-determined control parameters, the identifiability of the multiple to-be-determined control parameters is judged, and the identifiability represents the easy-to-determine degree of the to-be-determined control parameters; determining a plurality of control parameters to be determined according to the identifiability; and controlling the operation of the photovoltaic power generation system according to the control parameters. The problem that the stable operation of the photovoltaic power generation system cannot be controlled because all parameters of the inverter of the photovoltaic power generation system cannot be accurately obtained is solved.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic power generation, and in particular, to a method for determining control parameters of a photovoltaic power generation system, a determination device, a computer-readable storage medium, and an electronic device. Background Art

[0002] At present, renewable energy power generation technology has received extensive attention. Photovoltaic power generation can promote the active consumption of widely distributed solar energy resources and is an important means to build a modern intelligent clean power grid. As the capacity and scale of photovoltaic power generation grid-connected continue to increase, it may cause major technical problems in the current power grid, such as the stability and security of photovoltaic power generation grid-connected systems. Photovoltaic inverters are important equipment for photovoltaic grid-connected systems, and their dynamic performance affects the safe and stable operation of the entire photovoltaic power generation grid-connected system.

[0003] In actual engineering applications, photovoltaic grid-connected inverter controllers usually include phase-locked loops, voltage and current dual closed-loop controllers, etc. However, equipment manufacturers usually do not provide all accurate photovoltaic inverter control parameters. Currently, most of them use methods such as setting voltage drops on the grid-connected side or setting step disturbances of controller reference values ​​to stimulate controller dynamics, and then use heuristic algorithms such as particle swarm algorithms and genetic algorithms to obtain controller model parameters.

[0004] However, due to the high coupling between the photovoltaic inverter phase-locked loop and the current inner loop, and the tight cascade between the controller voltage outer loop and the current inner loop, previous methods have difficulty solving the identifiability problem of all controller parameters. Even if a heuristic algorithm with strong global optimization capability is used, it is impossible to obtain all the controller parameters stably and accurately. Summary of the invention

[0005] The main purpose of the present application is to provide a method for determining the control parameters of a photovoltaic power generation system, a determination device, a computer-readable storage medium and an electronic device, so as to at least solve the problem in the prior art that due to the high coupling of different types of parameters of the photovoltaic power generation system inverter, all parameters of the photovoltaic power generation system inverter cannot be accurately obtained, and thus the stable operation of the photovoltaic power generation system cannot be controlled.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for determining control parameters of a photovoltaic power generation system is provided, wherein the photovoltaic power generation system has an inverter, and comprises: obtaining a plurality of control parameters to be determined of the inverter; respectively calculating the absolute sensitivities of the plurality of control parameters to be determined when a preset condition is satisfied, wherein the preset condition is to perturb different observed variables of the inverter, and the plurality of control parameters to be determined have the corresponding absolute sensitivity in each disturbance; judging the identifiability of the plurality of control parameters to be determined according to the absolute sensitivities corresponding to the plurality of control parameters to be determined, wherein the identifiability characterizes the degree to which the control parameters to be determined are easy to be determined; determining the plurality of control parameters to be determined according to the identifiability; and controlling the operation of the photovoltaic power generation system according to the control parameters.

[0007] Optionally, the determination method further includes: establishing a control model of an inverter of a photovoltaic power generation system: ,in, and is the conversion value of the three-phase measured voltage at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the three-phase measured current at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the inverter output three-phase voltage in the dq0 coordinate system; L is the inductance between the inverter output and the PCC measurement point; is the phase-locked loop angular frequency output; according to the control model, the control parameter to be determined is determined.

[0008] Optionally, respectively calculating the absolute sensitivities of the multiple control parameters to be determined includes: determining the absolute sensitivities of the multiple control parameters to be determined according to a formula of the absolute sensitivity, where the formula of the absolute sensitivity is: , where S is the absolute sensitivity of the parameter, O(x) is the simulation output of the control model of the photovoltaic power generation system inverter, is the parameter to be analyzed, is the parameter increment size, is the actual value of the parameter.

[0009] Optionally, the multiple control parameters to be determined are determined according to the identifiability, including: perturbing different observed variables, selecting the control parameter with the highest identifiability among the multiple control parameters to be determined as the determination object, and determining the multiple control parameters to be determined in turn.

[0010] Optionally, completing the determination of the multiple control parameters to be determined includes: obtaining multiple groups of random combination samples of the multiple control parameters to be determined, the random combination samples including the determination object; identifying the random combination samples according to a standard particle swarm algorithm to obtain multiple groups of parameter samples of the determination object; iteratively screening the parameter samples according to an iterative algorithm to obtain an identification result of the determination object, thereby completing the determination of the control parameters to be determined.

[0011] Optionally, according to an iterative algorithm, the parameter samples are iteratively screened to obtain the identification result of the determined object, including: an acquisition step: obtaining a preset number of clusters of the iterative algorithm; a control step: grouping multiple groups of the random combination samples according to the preset number of clusters, and setting a group of the random combination samples with the most parameters in the grouped multiple groups of random combination samples as reference class samples; a calculation step: respectively calculating multiple concentrations of the reference class samples and other multiple random combination samples; a first judgment step: judging whether each of the concentrations is greater than a first preset threshold to obtain a first judgment result, and if the first judgment result indicates yes, eliminating the random combination samples whose concentrations are greater than the first preset threshold, and setting the remaining The random combination sample and the reference class sample are merged to form a new random combination sample; the second judgment step: judge whether the distance between the maximum parameter in the new random combination sample and the central parameter of the random combination sample is greater than or equal to the second preset threshold, and whether the distance between the minimum parameter and the central parameter of the random combination sample is greater than or equal to the second preset threshold, and obtain a second judgment result, wherein the central parameter is a parameter with an intermediate value in the random combination sample; a loop step: when the second judgment result indicates no, the acquisition step, the control step, the calculation step, the first judgment step and the second judgment step are looped at least once until the second judgment result indicates yes, and the identification result of the determined object is obtained.

[0012] Optionally, the multiple control parameters to be determined include: a phase-locked loop proportional coefficient, a phase-locked loop integral coefficient, a voltage outer loop proportional coefficient, a voltage outer loop integral coefficient, a current inner loop proportional coefficient and a current inner loop integral coefficient.

[0013] According to another aspect of the present application, a device for determining control parameters of a photovoltaic power generation system is provided, wherein the photovoltaic power generation system has an inverter, and comprises: an acquisition module, used for acquiring a plurality of control parameters to be determined of the inverter; a first control module, used for respectively calculating the absolute sensitivities of the plurality of control parameters to be determined when a preset condition is satisfied, wherein the preset condition is to perturb different observed variables of the inverter, and the plurality of control parameters to be determined have the corresponding absolute sensitivity in each disturbance; a judgment module, used for judging the identifiability of the plurality of control parameters to be determined according to the absolute sensitivities corresponding to the plurality of control parameters to be determined, wherein the identifiability characterizes the degree to which the control parameters to be determined are easy to be determined; a first determination module, used for determining the plurality of control parameters to be determined according to the identifiability; and a second control module, used for controlling the operation of the photovoltaic power generation system according to the control parameters.

[0014] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods for determining control parameters of a photovoltaic power generation system.

[0015] According to another aspect of the present application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for determining control parameters of a photovoltaic power generation system for executing any one of the above-described methods.

[0016] Applying the technical solution of the present application, the above-mentioned method for determining the control parameters of the photovoltaic power generation system first obtains multiple control parameters to be determined of the inverter of the photovoltaic power generation system, selects the observed variables of the inverter, and controls the observed variables of the inverter to perturb. In the case of the observed variables being perturbed, the sensitivity of the multiple control parameters to be determined is calculated, and the identifiability of the control parameters to be determined is judged according to the sensitivity, that is, the degree to which the control parameters to be determined are easily determined and selected, and the control parameters to be determined with the highest identifiability in each disturbance process are selected, and the selected control parameters to be determined are determined. After multiple disturbances, all the multiple control parameters to be determined of the inverter can be determined, and according to the control parameters, the photovoltaic power generation system can be controlled to operate more stably. The problem that all the parameters of the inverter of the photovoltaic power generation system cannot be accurately obtained due to the high coupling of different types of parameters of the inverter of the photovoltaic power generation system in the prior art, and thus the problem that the photovoltaic power generation system cannot be controlled to operate stably is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 A hardware structure block diagram of a mobile terminal for executing a method for determining control parameters of a photovoltaic power generation system provided in an embodiment of the present application is shown;

[0019] Figure 2 A schematic diagram of a process for determining a control parameter of a photovoltaic power generation system provided in accordance with an embodiment of the present application is shown;

[0020] Figure 3 The q-axis component of the grid-connected voltage of a photovoltaic power generation system provided according to an embodiment of the present application is shown. Schematic diagram of the waveform of time-amplitude;

[0021] Figure 4 A schematic diagram of an execution flow of a disturbance generating device for a photovoltaic power generation system provided according to an embodiment of the present application is shown;

[0022] Figure 5 The current diagram of the grid-connected side of a photovoltaic power generation system provided in accordance with an embodiment of the present application is shown. About the time-amplitude waveform diagram;

[0023] Figure 6 A schematic diagram of a waveform of a reactive power measurement signal Q on the grid side of a photovoltaic power generation system provided according to an embodiment of the present application with respect to time-amplitude is shown;

[0024] Figure 7 A waveform diagram of time-amplitude of voltage measurement of a DC capacitor on the grid-connected side of a photovoltaic power generation system provided in accordance with an embodiment of the present application is shown;

[0025] Figure 8 The actual voltage measurement signal of the DC capacitor on the grid side of a photovoltaic power generation system provided in accordance with an embodiment of the present application is shown. Schematic diagram of the waveform of time-amplitude;

[0026] Fig. 9 The phase-locked loop control parameters of a photovoltaic power generation system provided in accordance with an embodiment of the present application are shown. Schematic diagram of screening results;

[0027] Fig.10 The phase-locked loop control parameters of a photovoltaic power generation system provided in accordance with an embodiment of the present application are shown. Schematic diagram of screening results;

[0028] Fig.11 The current inner loop control parameters of a photovoltaic power generation system provided according to an embodiment of the present application are shown. Schematic diagram of screening results;

[0029] Fig.12 The current inner loop control parameters of a photovoltaic power generation system provided according to an embodiment of the present application are shown. Schematic diagram of screening results;

[0030] Fig.13 A schematic diagram of a device for determining control parameters of a photovoltaic power generation system provided according to an embodiment of the present application is shown.

[0031] The above drawings include the following reference numerals:

[0032] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0033] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0034] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] As introduced in the background technology, in the prior art, the photovoltaic inverter phase-locked loop and the current inner loop are highly coupled, and the controller voltage outer loop and the current inner loop are tightly cascaded. It is difficult for previous methods to solve the identifiability problem of all controller parameters. Even if a heuristic algorithm with strong global optimization capability is used, it is impossible to stably and accurately obtain all the parameters of the controller.

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0038] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal of a method for determining control parameters of a photovoltaic power generation system according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0039] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for determining the control parameters of the photovoltaic power generation system in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0040] In this embodiment, a method for determining control parameters of a photovoltaic power generation system running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0041] Figure 2 FIG. 1 is a flow chart of a method for determining control parameters of a photovoltaic power generation system according to an embodiment of the present application. Figure 2 As shown, the photovoltaic power generation system has an inverter, and the method comprises the following steps:

[0042] Step S201, obtaining a plurality of control parameters to be determined of the inverter;

[0043] Specifically, the parameters of the inverter that need to be determined are acquired so as to subsequently screen the control parameters to be determined.

[0044] Step S202, when the preset conditions are met, respectively calculate the absolute sensitivities of the above-mentioned multiple control parameters to be determined, and the above-mentioned preset conditions are to disturb different observed variables of the above-mentioned inverter, and the above-mentioned multiple control parameters to be determined have the corresponding above-mentioned absolute sensitivity in the case of each disturbance.

[0045] Specifically, multiple types of system disturbances are set to fully stimulate the dynamic characteristics of the inverter phase-locked loop parameters, voltage outer loop parameters and current inner loop parameters, and observe the dynamic output of the observed variables of the system inverter. The above-mentioned disturbance steps include: S2021, setting the grid-connected side voltage drop disturbance 1 of the photovoltaic power generation system connected to the inverter. A three-phase short-circuit fault with a duration of 0.05s is set on the grid-connected side transmission line to cause a system voltage drop and stimulate the dynamic characteristics of the inverter phase-locked loop. Figure 3 The q-axis component of the grid-connected voltage is given by Regarding the time-amplitude waveform; S2022, set the grid-connected side current measurement disturbance 2. First, use Figure 4 The digital signal processor (DSP) in the disturbance generator obtains the actual grid-connected current input by the actual signal of the generator. The steady-state component is preset to the amplitude through the digital-to-analog converter (D / A) , and the step measurement current disturbance signal (preset disturbance signal) with a duration of 0.05s, transmits the preset disturbance signal to the channel switch, and the actual measurement signal input by the actual signal is also transmitted to the channel switch. Then, the generator sends a channel conversion instruction, and the DSP outputs the set measurement current disturbance signal from the output end of the disturbance generator to the input end of the inverter current inner loop through the channel switch. At the same time, in order to decouple the inner and outer loops of the inverter and stabilize the inverter voltage at the same time, the voltage of the signal at the outer loop input end is , shielding the inverter voltage outer loop action, disturbing the grid-connected current Regarding the time-amplitude waveform Figure 5 shown. Figure 6 A waveform diagram of the reactive power measurement signal Q on the grid side with respect to time-amplitude is given; S2023, setting the voltage measurement disturbance 3 of the DC capacitor. Figure 4 The disturbance generating device shown in the figure obtains the steady-state signal of the DC side capacitance measurement. And through the D / A converter amplitude , and the step disturbance lasts for 0.05s. Then, the generator sends a channel switching instruction, and the DSP transmits the voltage disturbance signal of the set capacitor from the output end of the disturbance generator to the outer loop input end of the inverter voltage through the channel switching switch, such as Figure 7As shown, the waveform of the voltage measurement of the disturbed 3 DC capacitor with respect to time-amplitude. Figure 8 The actual measurement signal of the DC capacitor voltage is given A schematic diagram of a time-amplitude waveform.

[0046] Step S203: judging the identifiability of the control parameters to be determined according to the absolute sensitivities corresponding to the control parameters to be determined, wherein the identifiability represents the degree to which the control parameters to be determined are easy to be determined.

[0047] Specifically, the absolute sensitivity of each control parameter of the inverter under different disturbances and observation variables is calculated. The parameter offset in the parameter absolute sensitivity calculation formula is It is set to 10%. At the same time, three practical and easy-to-measure observation variables are selected for inverter control parameter sensitivity analysis and the distinguishability of multiple control parameters are analyzed. A step-by-step identification strategy for control parameters is designed. The observation variables include the q-axis component of the grid-connected side voltage mentioned above. , the reactive power measurement signal Q and the actual voltage measurement signal of the DC capacitor .

[0048] Step S204, determining the multiple control parameters to be determined according to the identifiability;

[0049] Specifically, in the process of each group of disturbances to the above-mentioned observed variables, the identifiability of the above-mentioned control parameters to be determined is observed. For example, in the case of the above-mentioned disturbance 1, the phase-locked loop control parameters have a larger or more obvious sensitivity relative to the control parameters of the current inner loop and the control parameters of the voltage outer loop, and the phase-locked loop control parameters can be clearly screened out. In the case of the above-mentioned disturbance 1, the phase-locked loop control parameters have a higher identifiability.

[0050] Step S205: controlling the operation of the photovoltaic power generation system according to the control parameters.

[0051] Specifically, equipment manufacturers usually do not provide all accurate photovoltaic inverter control parameters. After all the above control parameters are confirmed, the above photovoltaic power generation system can operate more stably and accurately.

[0052] Through the above-mentioned method for determining the control parameters of the photovoltaic power generation system, firstly, a plurality of control parameters to be determined of the inverter of the photovoltaic power generation system are obtained, the observed variables of the inverter are selected, and the observed variables of the inverter are controlled to be disturbed. When the observed variables are disturbed, the sensitivity of the plurality of control parameters to be determined is calculated, and the identifiability of the control parameters to be determined is judged according to the sensitivity, that is, the degree to which the control parameters to be determined are easily determined and selected, and the control parameters to be determined with the highest identifiability in each disturbance process are selected, and the selected control parameters to be determined are determined. After multiple disturbances, the plurality of control parameters to be determined of the inverter can be determined, and according to the control parameters, the photovoltaic power generation system can be controlled to operate more stably. The problem that all parameters of the inverter of the photovoltaic power generation system cannot be accurately obtained due to the high coupling of different types of parameters of the inverter of the photovoltaic power generation system in the prior art, and thus the problem that the photovoltaic power generation system cannot be controlled to operate stably is solved.

[0053] In some optional implementations, the above determination method further includes: establishing a control model of the photovoltaic power generation system inverter:

[0054] ,

[0055] in, and is the conversion value of the three-phase measured voltage at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the three-phase measured current at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the inverter output three-phase voltage in the dq0 coordinate system; L is the inductance between the inverter output and the PCC measurement point; is the phase-locked loop angular frequency output; according to the above control model, the above control parameters to be determined are determined.

[0056] In the above optional implementation manner, the above control parameters to be determined include phase-locked loop control parameters, current inner loop control parameters and voltage outer loop control parameters, wherein:

[0057] Phase-locked loop transfer function:

[0058] ,

[0059] in, and They are the proportional coefficient and integral coefficient of the phase-locked loop PI controller respectively.

[0060] Voltage outer loop control transfer function:

[0061] ,

[0062] in, is the grid-connected current d-axis reference value generated by the voltage outer loop PI controller; is the DC capacitor voltage, is the DC capacitor voltage reference value, which is 500V; and They are the proportional coefficient and integral coefficient of the voltage outer loop PI controller respectively.

[0063] Current inner loop control transfer function:

[0064] ,

[0065] in, and They are the three-phase rectifier bridge input voltages in the dq0 coordinate system; is the steady-state frequency of the system, which is 60Hz; is the q-axis reference value of the grid-connected current, which is 0; and They are the proportional coefficient and integral coefficient of the current inner loop PI controller respectively.

[0066] In the photovoltaic power generation system connected to the inverter, there are a total of 6 control parameters that need to be identified, namely: Phase-locked loop PI controller parameters and , voltage outer loop PI controller parameters and , current inner loop PI controller parameters and .

[0067] In some optional implementations, respectively calculating the absolute sensitivities of the plurality of control parameters to be determined includes: determining the absolute sensitivities of the plurality of control parameters to be determined according to the formula of the absolute sensitivity, wherein the formula of the absolute sensitivity is:

[0068] ,

[0069] Among them, S is the absolute sensitivity of the parameter, O(x) is the simulation output of the control model of the photovoltaic power generation system inverter, is the parameter to be analyzed, is the parameter increment size, is the actual value of the parameter.

[0070] In the above optional implementation manner, the parameter offset in the parameter absolute sensitivity calculation formula is It is set to 10%, and three practical and easy-to-measure observation variables are selected for inverter control parameter sensitivity analysis. Table 1 gives the sensitivity calculation results of the inverter control parameters.

[0071] Table 1

[0072]

[0073] In some optional embodiments, based on the above-mentioned identifiability, the above-mentioned multiple control parameters to be determined are determined, including: perturbing different of the above-mentioned observed variables, selecting the control parameter with the highest identifiability among the above-mentioned multiple control parameters to be determined as the determination object, and determining the multiple control parameters to be determined in turn.

[0074] In the above optional implementation, the distinguishability of multiple control parameters is analyzed, and a step-by-step identification strategy for control parameters is designed. It can be seen from Table 1 that the sensitivity values ​​of the phase-locked loop, voltage outer loop and current inner loop control parameters under three disturbances are quite different. The phase-locked loop control parameters have a relatively large sensitivity under disturbance 1, and the current inner loop control parameters have a relatively large sensitivity under disturbance 2, while the sensitivity of the voltage outer loop and inner loop parameters is not much different from other parameters. Therefore, in order to improve the identifiability of the six control parameters of the inverter, a step-by-step identification strategy for control parameters is designed, specifically: First, under disturbance 1, the q-axis component signal of the grid-connected side voltage is used as the input signal. As observation variables, identify the phase-locked loop control parameters and Then, under disturbance 2, the reactive power measurement signal Q on the grid side is used as the observed variable to identify the current inner loop control parameters and Finally, under disturbance 3, the actual measured signal is the DC capacitor voltage. As the observed variable, identify the voltage outer loop control parameters and .

[0075] In some optional embodiments, the determination of the above-mentioned multiple control parameters to be determined is completed, including: obtaining multiple groups of random combination samples of the above-mentioned multiple control parameters to be determined, the above-mentioned random combination samples including the above-mentioned determination object; according to the standard particle swarm algorithm, the above-mentioned random combination samples are identified to obtain multiple groups of parameter samples of the above-mentioned determination object; according to the iterative algorithm, the above-mentioned parameter samples are iteratively screened to obtain the identification results of the above-mentioned determination object, and the determination of the above-mentioned control parameters to be determined is completed.

[0076] In the above optional implementation manner, under the grid-connected side voltage drop disturbance (disturbance 1), the steps of randomly taking values ​​of the voltage outer loop and current inner loop control parameters, identifying the phase-locked loop control parameters multiple times, and selecting the best identification result by iterative K-means algorithm include the following sub-steps:

[0077] S11, since the true value of the inverter control parameter is actually unknown, in order to reduce the impact of inaccurate voltage outer loop and current inner loop parameter values ​​on the independent identification of phase-locked loop control parameters, 50 groups of random combinations of voltage outer loop and current inner loop control parameters are set.

[0078] S12, under 50 groups of samples, the standard particle swarm algorithm is used to independently identify the phase-locked loop control parameters, the number of particles is taken as 20, and it is iterated 10 times to obtain 50 groups of identification result total samples of the phase-locked loop control parameters.

[0079] S13, using a cyclic K-means algorithm to screen out the sample cluster with the highest concentration from the 50 groups of total samples, and then taking the average value of the cluster samples with the highest concentration as the final identification result of the phase-locked loop control parameters. Fig. 9 The phase-locked loop control parameters are given Screening result diagram (number of identification results - identification value), Fig.10 The phase-locked loop control parameters are given The screening result diagram (number of identification results-identification value) and the final identification results of the two parameters are listed in Table 2.

[0080] The step of decoupling and identifying the current inner loop control parameters under the set inverter input terminal current measurement disturbance includes the following sub-steps:

[0081] S21, the phase-locked loop parameters are obtained by taking the identified results, setting 50 groups of random combinations of voltage outer loop control parameters, and then, under these 50 groups of samples, identifying and obtaining 50 groups of total samples of identification results of current inner loop control parameters;

[0082] S22, similarly, a cyclic K-means algorithm is used to obtain the final identification result of the current inner loop control parameter. Fig.11 The current inner loop control parameters are given Screening result diagram (number of identification results - identification value), Fig.12 The current inner loop control parameters are given The screening result diagram (number of identification results-identification value) and the final identification results of the two parameters are listed in Table 2.

[0083] Under the set inverter input terminal DC capacitor voltage measurement disturbance, the voltage outer loop control parameters are independently identified once, and the identification results of all control parameters of the inverter are obtained, all of which are listed in Table 2. As can be seen from Table 2, the identification results of all control parameters of the inverter are very accurate, indicating the feasibility of the method of the present invention.

[0084] Table 2

[0085]

[0086] In some optional embodiments, the parameter samples are iteratively screened according to an iterative algorithm to obtain the identification results of the determined objects, including: an acquisition step: obtaining the preset number of clusters of the iterative algorithm; a control step: grouping multiple groups of the random combination samples according to the preset number of clusters, and setting the group of random combination samples with the most parameters in the grouped multiple groups of random combination samples as reference class samples; a calculation step: respectively calculating multiple concentrations of the reference class samples and the other multiple random combination samples; a first judgment step: judging whether each of the above concentrations is greater than a first preset threshold value to obtain a first judgment result. If the first judgment result indicates yes, the random combination samples with a concentration greater than the first preset threshold value are eliminated, and the reference class samples are set as reference class samples. The remaining random combination samples and the reference class samples are merged to form a new random combination sample; the second judgment step: judge whether the distance between the maximum parameter in the new random combination sample and the central parameter of the random combination sample is greater than or equal to the second preset threshold, and whether the distance between the minimum parameter and the central parameter of the random combination sample is greater than or equal to the second preset threshold, and obtain a second judgment result, the central parameter is a parameter with an intermediate value in the random combination sample; loop step: when the second judgment result indicates no, loop at least once the acquisition step, the control step, the calculation step, the first judgment step and the second judgment step, until the second judgment result indicates yes, to obtain the identification result of the determined object.

[0087] In the above optional implementation, the step of using the above cyclic K-means algorithm to screen out the best identification result includes: obtaining the preset number of clusters of the above iterative algorithm, determining the total sample of identification results of the parameter to be identified; if the number of K-means clusters is set to 3, the initial cluster center is set to a random value, and clustering is started; the class with the most sample individuals is selected as the reference class, and the distance (concentration) to the other two classes is calculated; if the relative distance does not exceed A=1% (the first preset threshold), the three groups are merged into one group, and the K-means algorithm is iterated until the maximum individual and the minimum individual in the new sample are both within B=1% (the second preset threshold) from the sample center, and the average value of the final retained sample is used as the final identification result of the parameter to be identified; if the condition that the maximum individual and the minimum individual in the new sample are both within B=1% from the sample center is not met, the above clustering, reference sample selection and concentration calculation steps are re-executed until the conditions are met and the final sample is output. If the relative distance exceeds A=1%, the excess class whose relative distance exceeds A=1% (the first preset threshold) is eliminated, and the remaining classes are merged to form a new sample; the K-means algorithm is iterated until the maximum individual and the minimum individual in the new sample are both within B=1% (the second preset threshold) from the sample center, and the average value of the final retained sample is used as the final identification result of the parameter to be identified; if the condition that the maximum individual and the minimum individual in the new sample are both within B=1% from the sample center is not met, the above clustering, reference sample selection and concentration calculation steps are re-executed until the conditions are met and the final sample is output.

[0088] In some optional implementations, the multiple control parameters to be determined include: a phase-locked loop proportional coefficient, a phase-locked loop integral coefficient, a voltage outer loop proportional coefficient, a voltage outer loop integral coefficient, a current inner loop proportional coefficient and a current inner loop integral coefficient.

[0089] In the above optional implementation, the photovoltaic inverter is a voltage source inverter, and the inverter main circuit is a three-phase bridge structure. The inverter phase-locked loop is a PI control structure, and the inverter controller adopts a voltage and current double closed-loop PI control structure. The parameters of the parameters are as described above. The simulation system is built on the Matlab2019a / Simulink software platform. The components and parameters use the photovoltaic grid-connected power generation system example provided by the software, and the photovoltaic power generation system operates under standard test conditions. The true value and value range of the inverter control parameters to be identified are shown in Table 3. The control parameters to be determined of the inverter include: phase-locked loop proportional coefficient, phase-locked loop integral coefficient, voltage outer loop proportional coefficient, voltage outer loop integral coefficient, current inner loop proportional coefficient and current inner loop integral coefficient. The above-mentioned control parameters to be determined are also called control parameters to be identified, and their true values ​​and value ranges are shown in Table 3.

[0090] Table 3

[0091]

[0092] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0093] The embodiment of the present application also provides a device for determining the control parameters of a photovoltaic power generation system. It should be noted that the device for determining the control parameters of a photovoltaic power generation system in the embodiment of the present application can be used to execute the method for determining the control parameters of a photovoltaic power generation system provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and those that have been described will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0094] The following is an introduction to the device for determining control parameters of a photovoltaic power generation system provided in an embodiment of the present application.

[0095] Fig.13 Schematic diagram of a device for determining control parameters of a photovoltaic power generation system according to an embodiment of the present application. Fig.13 As shown, the photovoltaic power generation system has an inverter, and the device includes: an acquisition module 100, used to acquire multiple control parameters to be determined of the inverter; a first control module 200, used to respectively calculate the absolute sensitivity of the multiple control parameters to be determined when a preset condition is met, and the preset condition is to perturb different observed variables of the inverter, and the multiple control parameters to be determined have the corresponding absolute sensitivity in each disturbance; a judgment module 300, used to judge the identifiability of the multiple control parameters to be determined according to the absolute sensitivity corresponding to the multiple control parameters to be determined, and the identifiability represents the degree to which the control parameters to be determined are easy to be determined; a first determination module 400, used to determine the multiple control parameters to be determined according to the identifiability; a second control module 500, used to control the operation of the photovoltaic power generation system according to the control parameters.

[0096] The above-mentioned photovoltaic power generation system control parameter determination device of the present application includes an acquisition module, a first control module, a judgment module, a first determination module and a second control module, wherein the acquisition module is used to acquire multiple control parameters to be determined of the inverter of the above-mentioned photovoltaic power generation system; the first control module is used to select the observed variables of the above-mentioned inverter, and control the observed variables of the above-mentioned inverter to be disturbed, and calculate the sensitivity of multiple control parameters to be determined when the observed variables are disturbed; the judgment module is used to judge the identifiability of the control parameters to be determined according to the sensitivity, that is, to judge the degree to which the control parameters to be determined are easy to be determined and selected; the first determination module is used to select the control parameters to be determined with the highest identifiability in each disturbance process, and determine the selected control parameters to be determined. After multiple disturbances, all the multiple control parameters to be determined of the above-mentioned inverter can be determined; the second control module is used to control the above-mentioned photovoltaic power generation system to operate more stably according to the above-mentioned control parameters. The problem that all parameters of the inverter of the photovoltaic power generation system cannot be accurately obtained due to the high coupling of different types of parameters of the inverter of the photovoltaic power generation system in the prior art, and thus the problem that the photovoltaic power generation system cannot be controlled to operate stably is solved.

[0097] In some optional solutions, the above-mentioned determination device further includes a construction module and a second determination module, and the construction module is used to establish a control model of the photovoltaic power generation system inverter: ,in, and is the conversion value of the three-phase measured voltage at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the three-phase measured current at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the inverter output three-phase voltage in the dq0 coordinate system; L is the inductance between the inverter output and the PCC measurement point; is the phase-locked loop angular frequency output; the second determination module is used to determine the above-mentioned control parameters to be determined according to the above-mentioned control model.

[0098] In some optional schemes, the calculation step includes a first sub-determination module, which calculates the absolute sensitivity of the above-mentioned multiple control parameters to be determined respectively, including: the first sub-determination module is used to calculate according to the above-mentioned absolute sensitivity formula to determine the absolute sensitivity of the above-mentioned multiple control parameters to be determined, and the above-mentioned absolute sensitivity formula is: , where S is the absolute sensitivity of the parameter, O(x) is the simulation output of the control model of the photovoltaic power generation system inverter, is the parameter to be analyzed, is the parameter increment size, is the actual value of the parameter.

[0099] In some optional schemes, the first determination module includes a disturbance module, which determines the above-mentioned multiple control parameters to be determined according to the above-mentioned identifiability, including: the above-mentioned disturbance module is used to perturb different of the above-mentioned observed variables, select the control parameter with the highest identifiability among the above-mentioned multiple control parameters to be determined as the determination object, and determine the multiple control parameters to be determined in turn.

[0100] An optional scheme, the second determination module includes a first sub-acquisition module, a first sub-determination module and a screening module, wherein the first sub-acquisition module is used to determine the above-mentioned multiple control parameters to be determined, including: obtaining multiple groups of random combination samples of the above-mentioned multiple control parameters to be determined, the above-mentioned random combination samples include the above-mentioned determination object; the first sub-determination module is used to identify the above-mentioned random combination samples according to the standard particle swarm algorithm to obtain multiple groups of parameter samples of the above-mentioned determination object; the screening module is used to iteratively screen the above-mentioned parameter samples according to an iterative algorithm to obtain the identification results of the above-mentioned determination object, and complete the determination of the above-mentioned control parameters to be determined.

[0101] An optional solution, the above-mentioned screening module includes a second sub-acquisition module, a first sub-control module, a first sub-calculation module, a first sub-judgment module, a second sub-judgment module and a first sub-loop module, and according to the iterative algorithm, iterative screening of the above-mentioned parameter samples is completed to obtain the identification result of the above-mentioned determined object, including: the second sub-acquisition module is used to execute the acquisition step: obtain the preset clustering number of the above-mentioned iterative algorithm; the first sub-control module is used to execute the control step: according to the above-mentioned preset clustering number, multiple groups of the above-mentioned random combination samples are grouped, and the group of the above-mentioned random combination samples with the most parameters in the grouped multiple groups of random combination samples is set as a reference class sample; the first sub-calculation module is used to execute the calculation step: respectively calculate the multiple concentrations of the above-mentioned reference class samples and the other multiple random combination samples; the first sub-judgment module is used to execute the first judgment step: judge whether each of the above-mentioned concentrations is greater than the first preset threshold value, and obtain a first judgment result, and the above-mentioned first judgment result indicates If the above-mentioned random combination samples are indicated as yes, the above-mentioned random combination samples whose concentration is greater than the above-mentioned first preset threshold are eliminated, and the remaining above-mentioned random combination samples and the above-mentioned reference class samples are merged to form the above-mentioned new random combination samples; the second sub-judgment module is used to execute the second judgment step: judge whether the distance between the maximum parameter in the above-mentioned new random combination sample and the central parameter of the above-mentioned random combination sample is greater than or equal to the second preset threshold, and whether the distance between the minimum parameter and the central parameter of the above-mentioned random combination sample is greater than or equal to the above-mentioned second preset threshold, and obtain the second judgment result, and the above-mentioned central parameter is the parameter with an intermediate value in the above-mentioned random combination sample; the first sub-loop module is used to execute the loop step: if the above-mentioned second judgment result indicates no, the above-mentioned acquisition step, the above-mentioned control step, the above-mentioned calculation step, the above-mentioned first judgment step and the above-mentioned second judgment step are looped at least once, until the above-mentioned second judgment result indicates yes, and the identification result of the above-mentioned determined object is obtained.

[0102] In an optional solution, the multiple control parameters to be determined in the acquisition module include: a phase-locked loop proportional coefficient, a phase-locked loop integral coefficient, a voltage outer loop proportional coefficient, a voltage outer loop integral coefficient, a current inner loop proportional coefficient and a current inner loop integral coefficient.

[0103] The above-mentioned photovoltaic power generation system control parameter determination device includes a processor and a memory, and the above-mentioned first acquisition module and the like are stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions. The above-mentioned modules are all located in the same processor; or, the above-mentioned modules are located in different processors in any combination.

[0104] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters are adjusted to solve the problem in the prior art that due to the high coupling of different types of parameters of the photovoltaic power generation system inverter, all parameters of the photovoltaic power generation system inverter cannot be accurately obtained, and thus the photovoltaic power generation system cannot be controlled to operate stably.

[0105] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0106] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for determining the control parameters of the photovoltaic power generation system.

[0107] Specifically, the method for determining the control parameters of the photovoltaic power generation system includes:

[0108] Step S201, obtaining a plurality of control parameters to be determined of the inverter;

[0109] Step S202, when a preset condition is met, respectively calculating the absolute sensitivities of the plurality of control parameters to be determined, wherein the preset condition is that different observed variables of the inverter are disturbed, and the plurality of control parameters to be determined have the corresponding absolute sensitivity in each disturbance case;

[0110] Step S203: judging the identifiability of the control parameters to be determined according to the absolute sensitivities corresponding to the control parameters to be determined, wherein the identifiability represents the degree to which the control parameters to be determined are easy to be determined.

[0111] Step S204, determining the multiple control parameters to be determined according to the identifiability;

[0112] Step S205: controlling the operation of the photovoltaic power generation system according to the control parameters.

[0113] An embodiment of the present invention provides a processor, and the processor is used to run a program, wherein the method for determining control parameters of the photovoltaic power generation system is executed when the program is run.

[0114] Specifically, the method for determining the control parameters of the photovoltaic power generation system includes:

[0115] Step S201, obtaining a plurality of control parameters to be determined of the inverter;

[0116] Step S202, when a preset condition is met, respectively calculating the absolute sensitivities of the plurality of control parameters to be determined, wherein the preset condition is that different observed variables of the inverter are disturbed, and the plurality of control parameters to be determined have the corresponding absolute sensitivity in each disturbance case;

[0117] Step S203: judging the identifiability of the control parameters to be determined according to the absolute sensitivities corresponding to the control parameters to be determined, wherein the identifiability represents the degree to which the control parameters to be determined are easy to be determined.

[0118] Step S204, determining the multiple control parameters to be determined according to the identifiability;

[0119] Step S205: controlling the operation of the photovoltaic power generation system according to the control parameters.

[0120] An embodiment of the present invention provides an electronic device, the device comprising a processor, a memory, and a program stored in the memory and executable on the processor, and when the processor executes the program, at least the following steps are implemented:

[0121] Step S201, obtaining a plurality of control parameters to be determined of the inverter;

[0122] Step S202, when a preset condition is met, respectively calculating the absolute sensitivities of the plurality of control parameters to be determined, wherein the preset condition is that different observed variables of the inverter are disturbed, and the plurality of control parameters to be determined have the corresponding absolute sensitivity in each disturbance case;

[0123] Step S203: judging the identifiability of the control parameters to be determined according to the absolute sensitivities corresponding to the control parameters to be determined, wherein the identifiability represents the degree to which the control parameters to be determined are easy to be determined.

[0124] Step S204, determining the multiple control parameters to be determined according to the identifiability;

[0125] Step S205: controlling the operation of the photovoltaic power generation system according to the control parameters.

[0126] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0127] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps:

[0128] Step S201, obtaining a plurality of control parameters to be determined of the inverter;

[0129] Step S202, when a preset condition is met, respectively calculating the absolute sensitivities of the plurality of control parameters to be determined, wherein the preset condition is that different observed variables of the inverter are disturbed, and the plurality of control parameters to be determined have the corresponding absolute sensitivity in each disturbance case;

[0130] Step S203: judging the identifiability of the control parameters to be determined according to the absolute sensitivities corresponding to the control parameters to be determined, wherein the identifiability represents the degree to which the control parameters to be determined are easy to be determined.

[0131] Step S204, determining the multiple control parameters to be determined according to the identifiability;

[0132] Step S205: controlling the operation of the photovoltaic power generation system according to the control parameters.

[0133] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0134] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0135] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0136] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0138] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0139] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0140] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0141] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0142] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0143] 1) The method for determining the control parameters of the photovoltaic power generation system of the present application first obtains a plurality of control parameters to be determined of the inverter of the photovoltaic power generation system, selects the observed variables of the inverter, and controls the observed variables of the inverter to disturb. In the case of the disturbance of the observed variables, the sensitivity of the plurality of control parameters to be determined is calculated, and the identifiability of the control parameters to be determined is judged according to the sensitivity, that is, the degree to which the control parameters to be determined are easily determined and selected. The control parameters to be determined with the highest identifiability in each disturbance process are selected, and the selected control parameters to be determined are determined. After multiple disturbances, the plurality of control parameters to be determined of the inverter can be determined. According to the control parameters, the photovoltaic power generation system can be controlled to operate more stably. The problem that all the parameters of the inverter of the photovoltaic power generation system cannot be accurately obtained due to the high coupling of different types of parameters of the inverter of the photovoltaic power generation system in the prior art, and thus the stable operation of the photovoltaic power generation system cannot be controlled is solved.

[0144] 2) The device for determining the control parameters of the photovoltaic power generation system of the present application comprises an acquisition module, a first control module, a judgment module, a first determination module and a second control module, wherein the acquisition module is used to acquire multiple control parameters to be determined of the inverter of the photovoltaic power generation system; the first control module is used to select the observed variables of the inverter and control the observed variables of the inverter to be disturbed, and calculate the sensitivity of multiple control parameters to be determined when the observed variables are disturbed; the judgment module is used to judge the identifiability of the control parameters to be determined according to the sensitivity, that is, to judge the degree to which the control parameters to be determined are easy to be determined and selected; the first determination module is used to select the control parameters to be determined with the highest identifiability in each disturbance process, and determine the selected control parameters to be determined. After multiple disturbances, all the multiple control parameters to be determined of the inverter can be determined; the second control module is used to control the photovoltaic power generation system to operate more stably according to the control parameters. The problem that all the parameters of the inverter of the photovoltaic power generation system cannot be accurately obtained due to the high coupling of different types of parameters of the inverter of the photovoltaic power generation system in the prior art, and thus the problem that the photovoltaic power generation system cannot be controlled to operate stably is solved.

[0145] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining control parameters of a photovoltaic power generation system, wherein the photovoltaic power generation system has an inverter, characterized in that: include: Acquiring a plurality of control parameters to be determined of the inverter; Under the condition that a preset condition is met, respectively calculating the absolute sensitivities of the multiple control parameters to be determined, wherein the preset condition is that different observed variables of the inverter are disturbed, and the multiple control parameters to be determined have the corresponding absolute sensitivity under each disturbance; According to the absolute sensitivities corresponding to the multiple control parameters to be determined, determining the identifiability of the multiple control parameters to be determined, wherein the identifiability represents the degree to which the control parameters to be determined are easy to be determined; Determining the plurality of control parameters to be determined according to the identifiability; The operation of the photovoltaic power generation system is controlled according to the control parameters.

2. The determination method according to claim 1, characterized in that: The determination method further comprises: Establish the control model of the photovoltaic power generation system inverter: ， in, and is the conversion value of the three-phase measured voltage at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the three-phase measured current at the PCC on the grid-connected side of the photovoltaic power generation system in the dq0 coordinate system; and is the conversion value of the inverter output three-phase voltage in the dq0 coordinate system; L is the inductance between the inverter output and the PCC measurement point; is the phase-locked loop angular frequency output; The control parameter to be determined is determined according to the control model.

3. The determination method according to claim 1, characterized in that: Calculating the absolute sensitivities of the plurality of control parameters to be determined respectively, comprising: The absolute sensitivity of the plurality of control parameters to be determined is determined by calculating according to the absolute sensitivity formula, wherein the absolute sensitivity formula is: ， Among them, S is the absolute sensitivity of the parameter, O(x) is the simulation output of the control model of the photovoltaic power generation system inverter, is the parameter to be analyzed, is the parameter increment size, is the actual value of the parameter.

4. The determination method according to claim 1, characterized in that: Determining the plurality of control parameters to be determined according to the identifiability includes: The different observed variables are disturbed, the control parameter with the highest identifiability among the multiple control parameters to be determined is selected as the determination object, and the multiple control parameters to be determined are determined in turn.

5. The determination method according to claim 4, characterized in that: Determining the multiple control parameters to be determined includes: Acquire a plurality of groups of random combination samples of the plurality of control parameters to be determined, wherein the random combination samples include the determination object; According to the standard particle swarm algorithm, the random combination samples are identified to obtain multiple groups of parameter samples of the determined objects; According to the iterative algorithm, the parameter samples are iteratively screened to obtain the identification result of the determined object, and the control parameter to be determined is determined.

6. The determination method according to claim 5, characterized in that: According to the iterative algorithm, the parameter samples are iteratively screened to obtain the identification result of the determined object, including: Acquisition step: acquiring a preset number of clusters of the iterative algorithm; Control step: grouping the multiple groups of random combination samples according to the preset cluster number, and setting the group of random combination samples with the most parameters among the multiple groups of random combination samples as reference class samples; Calculation step: respectively calculating multiple concentrations of the reference sample and the other multiple random combination samples; The first judgment step: judging whether each of the concentrations is greater than a first preset threshold value, obtaining a first judgment result, and when the first judgment result indicates yes, eliminating the random combination samples whose concentrations are greater than the first preset threshold value, and merging the remaining random combination samples and the reference class samples to form a new random combination sample; The second judgment step: judging whether the distance between the maximum parameter in the new random combination sample and the central parameter of the random combination sample is greater than or equal to the second preset threshold, and whether the distance between the minimum parameter and the central parameter of the random combination sample is greater than or equal to the second preset threshold, and obtaining a second judgment result, wherein the central parameter is a parameter with an intermediate value in the random combination sample; Loop step: when the second judgment result indicates no, the acquisition step, the control step, the calculation step, the first judgment step and the second judgment step are looped at least once until the second judgment result indicates yes, thereby obtaining the identification result of the determined object.

7. The determination method according to claim 1, characterized in that: The multiple control parameters to be determined include: a phase-locked loop proportional coefficient, a phase-locked loop integral coefficient, a voltage outer loop proportional coefficient, a voltage outer loop integral coefficient, a current inner loop proportional coefficient and a current inner loop integral coefficient.

8. A device for determining control parameters of a photovoltaic power generation system, wherein the photovoltaic power generation system has an inverter, characterized in that: include: An acquisition module, used for acquiring a plurality of control parameters to be determined of the inverter; A first control module, configured to respectively calculate the absolute sensitivities of the plurality of control parameters to be determined when a preset condition is satisfied, wherein the preset condition is that different observed variables of the inverter are disturbed, and the plurality of control parameters to be determined have the corresponding absolute sensitivity in each disturbance case; A judging module, configured to judge the identifiability of the plurality of control parameters to be determined according to the absolute sensitivities corresponding to the plurality of control parameters to be determined, wherein the identifiability represents the degree to which the control parameters to be determined are easy to be determined; A first determination module, configured to determine the plurality of control parameters to be determined according to the identifiability; The second control module is used to control the operation of the photovoltaic power generation system according to the control parameters.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for determining control parameters of a photovoltaic power generation system according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for determining control parameters of a photovoltaic power generation system according to any one of claims 1 to 7.

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