Parameter identification method and device based on park energy system, equipment and medium

Abstract

The application relates to the field of new energy grid connection technology, and discloses a parameter identification method, device and equipment based on a park energy system and a medium, the method comprising: acquiring a plurality of to-be-identified parameters of the park energy system, the plurality of to-be-identified parameters comprising line resistance, line inductance, line capacitance, capacity of a wind power converter, capacity of a photovoltaic inverter, transformer short-circuit impedance, proportional gain coefficient of the photovoltaic inverter, integral gain coefficient of the photovoltaic inverter, control parameter of the wind power converter and harmonic attenuation coefficient; generating a comprehensive deviation corresponding to each parameter combination according to a comprehensive deviation function, selecting a parameter combination with the minimum comprehensive deviation as a target parameter combination of the park energy system, and completing grid connection of the park energy system and a public power grid according to the target parameter combination. The application can improve the identification efficiency of the target parameter combination of the park energy system, and the target parameter combination can provide strong guarantee for safe grid connection of the park energy system.

Description

Technical Field

[0001] This application relates to the field of new energy grid connection technology, and in particular to parameter identification methods, devices, equipment and media based on park energy systems. Background Technology

[0002] The power generation of the park's energy system is intermittent and fluctuates, which differs from the stable operation requirements of the public power grid. Therefore, it is necessary to determine the target parameter combination of the park's energy system in order to achieve coordinated operation between the park's energy system and the public power grid.

[0003] However, the identification of target parameter combinations for park energy systems has long relied on manual experience and item-by-item analysis. This approach not only requires engineers to spend a significant amount of time screening, comparing, and verifying multi-dimensional data, but also necessitates repeated debugging of different parameter combinations to verify feasibility, resulting in a lengthy and inefficient process. Therefore, how to identify target parameter combinations for park energy systems is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and medium for parameter identification based on a park energy system, in order to solve the aforementioned technical problem of how to identify the target parameter combination of a park energy system.

[0005] In a first aspect, embodiments of this application provide a parameter identification method based on a park energy system, applied to an identification device for the park energy system. The park energy system includes wind turbines equipped with wind power converters, photovoltaic equipment equipped with photovoltaic inverters, and load equipment. The parameter identification method includes:

[0006] Obtain the current status of the switch at the common connection point, which is the node that connects the park's energy system to the public power grid;

[0007] When the current state is closed, multiple parameters to be identified in the park's energy system are obtained. These parameters include line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, harmonic attenuation coefficient, and the transformer short-circuit impedance is the short-circuit impedance of the transformer matched with the load equipment.

[0008] The ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient are input into the sampling module to obtain multiple parameter combinations output by the sampling module.

[0009] Each parameter combination is input into the simulation model of the park's energy system to obtain simulation data for each parameter combination. From the simulation data of each parameter combination, the simulation values ​​of the output voltage, output current, output frequency, and total harmonic distortion of the simulation model under each parameter combination are obtained.

[0010] Based on the simulated values ​​of output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination, and the comprehensive deviation function, a comprehensive deviation is generated for each parameter combination. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system. The park's energy system is then connected to the public power grid based on the target parameter combination. The comprehensive deviation is used to measure the degree of comprehensive deviation of the parameter combination in four aspects: output voltage, output current, output frequency, and THD.

[0011] In one possible implementation of the first aspect, the ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient are input into a sampling module to obtain multiple parameter combinations output by the sampling module, including:

[0012] The ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient are used to form the value data. The value data and sampling instructions are transmitted to the sampling module. The sampling module processes the value data and acquisition instructions to obtain the sampling results. Multiple parameter combinations are obtained from the sampling results.

[0013] In one possible implementation of the first aspect, each parameter combination is input into a simulation model of the park's energy system to obtain simulation data for each parameter combination. From the simulation data for each parameter combination, the simulated values ​​of the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination are obtained, including:

[0014] Obtain the topology data and component parameter information of the park's energy system, input the topology data and component parameter information into the simulation tool, and generate a simulation model of the park's energy system through the simulation tool;

[0015] Each parameter combination is input into the simulation model of the park's energy system to obtain the output results of the simulation model. The simulation data of each parameter combination is obtained from the output results. From the simulation data of each parameter combination, the simulation values ​​of the output voltage, output current, output frequency, and total harmonic distortion of the simulation model under each parameter combination are obtained.

[0016] In one possible implementation of the first aspect, based on the simulated values ​​of the output voltage, output current, output frequency, total harmonic distortion (THD), and comprehensive deviation function of the simulation model under each parameter combination, a comprehensive deviation is generated for each parameter combination. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system. The grid connection between the park's energy system and the public power grid is then completed based on the target parameter combination, including:

[0017] The current signal of the park's energy system is collected by a distributed sensor network. Harmonic decomposition is performed on the current signal to obtain the effective value of the fundamental component and the effective value of the harmonic component. The effective values ​​of the fundamental component and the effective value of the harmonic component are substituted into the calculation formula of the total harmonic distortion rate to obtain the measured value of the total harmonic distortion rate of the park's energy system.

[0018] Based on the measured value of the total harmonic distortion (THD) of the park's energy system, the simulated value of the output voltage of the simulation model under each parameter combination, the simulated value of the output current of the simulation model under each parameter combination, the simulated value of the output frequency of the simulation model under each parameter combination, the simulated value of the THD of the simulation model under each parameter combination, and the comprehensive deviation function, a comprehensive deviation corresponding to each parameter combination is generated. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination of the park's energy system, and the target parameter combination is transmitted to the control module of the park's energy system.

[0019] The control module obtains the target values ​​of the proportional gain coefficient and integral gain coefficient of the photovoltaic inverter and the target values ​​of the control parameters of the wind power converter from the target parameter combination. It processes the target value of the proportional gain coefficient of the photovoltaic inverter to obtain the first control command, processes the target value of the integral gain coefficient of the photovoltaic inverter to obtain the second control command, and processes the target value of the control parameters of the wind power converter to obtain the third control command. By running the first and second control commands, the photovoltaic inverter in the park's energy system is connected to the public power grid. By running the third control command, the wind power converter in the park's energy system is connected to the public power grid.

[0020] In one possible implementation of the first aspect, the comprehensive deviation function is defined as follows:

[0021] ;

[0022] in, For the first The comprehensive deviation corresponding to the combination of parameters; the first The larger the overall deviation corresponding to each parameter combination, the more likely the simulation model is to be flawed. When all parameters are combined, the greater the overall deviation in output voltage, output current, output frequency, and total harmonic distortion (THD); The smaller the overall deviation corresponding to each parameter combination, the better the simulation model is. When combining these parameters, the smaller the overall deviation in output voltage, output current, output frequency, and total harmonic distortion (THD);

[0023] The simulation model is in the first... Simulated values ​​of output voltage under various parameter combinations;

[0024] This represents the measured output voltage of the park's energy system during grid connection.

[0025] For the simulation model in the first Simulated values ​​of output current under various parameter combinations;

[0026] This represents the measured value of the output current of the park's energy system during grid connection.

[0027] For the simulation model in the first Simulated values ​​of output frequency under various parameter combinations;

[0028] This represents the measured output frequency of the park's energy system during grid connection.

[0029] For the simulation model in the first Simulated values ​​of total harmonic distortion under various parameter combinations;

[0030] This is the measured value of the total harmonic distortion rate of the park's energy system during grid connection.

[0031] For voltage threshold, For current threshold, For frequency threshold, This is the distortion rate threshold; As the first weighting coefficient, This is the second weighting coefficient. This is the third weighting coefficient. It is the fourth weighting coefficient.

[0032] In one possible implementation of the first aspect, each parameter combination includes a sampled value of line resistance, a sampled value of line inductance, a sampled value of line capacitance, a sampled value of wind power converter capacity, a sampled value of photovoltaic inverter capacity, a sampled value of transformer short-circuit impedance, a sampled value of photovoltaic inverter proportional gain coefficient, a sampled value of photovoltaic inverter integral gain coefficient, a sampled value of wind power converter control parameter, and a sampled value of harmonic attenuation coefficient.

[0033] In one possible implementation of the first aspect, the park's energy system is an integrated energy system for a green energy park, which refers to a park that generates electricity using solar and wind power.

[0034] Secondly, embodiments of this application provide a parameter identification device based on a park energy system, applied to the identification equipment of the park energy system. The park energy system includes wind turbines equipped with wind power converters, photovoltaic equipment equipped with photovoltaic inverters, and load equipment, including:

[0035] The first acquisition module is used to acquire the current status of the switch of the common connection point, which is the node that connects the park's energy system to the public power grid.

[0036] The second acquisition module is used to acquire multiple parameters to be identified in the park's energy system when the current state is closed. The multiple parameters to be identified include line resistance, line inductance, line capacitance, capacity of wind power converter, capacity of photovoltaic inverter, transformer short-circuit impedance, proportional gain coefficient of photovoltaic inverter, integral gain coefficient of photovoltaic inverter, control parameters of wind power converter, harmonic attenuation coefficient, and transformer short-circuit impedance is the short-circuit impedance of the transformer matched with the load equipment.

[0037] The input module is used to input the ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient into the sampling module to obtain multiple parameter combinations output by the sampling module;

[0038] The third acquisition module is used to input each parameter combination into the simulation model of the park's energy system, obtain the simulation data of each parameter combination, and obtain the simulation value of the output voltage, the simulation value of the output current, the simulation value of the output frequency, and the simulation value of the total harmonic distortion rate of the simulation model under each parameter combination from the simulation data of each parameter combination.

[0039] The identification module is used to generate a comprehensive deviation for each parameter combination based on the simulated values ​​of the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination, as well as the comprehensive deviation function. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system. The park's energy system is then connected to the public power grid based on the target parameter combination. The comprehensive deviation is used to measure the degree of comprehensive deviation of the parameter combination in four aspects: output voltage, output current, output frequency, and THD.

[0040] Thirdly, embodiments of this application provide an identification device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the parameter identification method described in the first aspect above.

[0041] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the parameter identification method described in the first aspect above.

[0042] Fifthly, embodiments of this application provide a computer program product that, when run on an identification device, causes the identification device to execute the parameter identification method described in the first aspect above.

[0043] The beneficial effects of this application's embodiments are twofold. Firstly, based on the simulated values ​​of the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination, and the comprehensive deviation function, a comprehensive deviation is generated for each parameter combination. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system. The grid connection between the park's energy system and the public power grid is then completed based on the target parameter combination, which helps improve the efficiency of identifying the target parameter combination for the park's energy system. Secondly, the comprehensive deviation corresponding to the parameter combination... The larger the overall deviation, the greater the comprehensive deviation of the simulation model in terms of output voltage, output current, output frequency, and total harmonic distortion (THD) when using parameter combinations. The smaller the overall deviation of the parameter combinations, the smaller the comprehensive deviation of the simulation model in terms of output voltage, output current, output frequency, and THD when using parameter combinations. Selecting the parameter combination with the smallest overall deviation as the target parameter combination for the park's energy system and completing the grid connection of the park's energy system with the public power grid based on the target parameter combination can ensure that the operating status of the park's energy system connected to the public power grid is highly consistent with the dispatch requirements of the public power grid, reducing the grid connection impact caused by parameter mismatch. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is an application scenario diagram of the parameter recognition method provided in the embodiments of this application;

[0046] Figure 2 This is a flowchart illustrating the parameter identification method provided in the embodiments of this application;

[0047] Figure 3 A flowchart illustrating the implementation of S205 provided in this application embodiment;

[0048] Figure 4 A schematic block diagram of the parameter recognition device provided in the embodiments of this application;

[0049] Figure 5 This is a schematic diagram of the structure of the identification device provided in an embodiment of this application. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0051] The parameter recognition method provided in this application can be applied to recognition devices, including but not limited to servers, mobile phones, tablets, laptops, and personal digital assistants. This application does not impose any restrictions on the specific type of recognition device.

[0052] Please see Figure 1 , Figure 1 The application scenario diagram of the parameter recognition method provided in the embodiments of this application is described in detail below:

[0053] The parameter identification method is applied to the identification equipment of the park's energy system, which includes wind turbines with wind power converters, photovoltaic equipment with photovoltaic inverters, and load equipment.

[0054] The park's energy system is a comprehensive energy system for green energy parks, which are parks that rely on solar and wind power for power generation.

[0055] In this embodiment, the park's energy system is connected to the public power grid. This connection mode promotes the efficient use of clean energy. The power generated by wind turbines and photovoltaic equipment can be used primarily for their own purposes, and any surplus can be connected to the public power grid for use in other areas, thereby reducing fossil energy consumption and carbon emissions.

[0056] Please see Figure 2 , Figure 2 This is a flowchart illustrating the parameter identification method provided in this application embodiment. This method can be applied to the identification equipment of a park energy system, which includes wind turbines equipped with wind power converters, photovoltaic equipment equipped with photovoltaic inverters, and load equipment.

[0057] like Figure 2 As shown, the parameter identification method provided in this application includes the following steps, which are detailed below:

[0058] S201, obtain the current status of the switch of the common connection point, which is the node that connects the park's energy system to the public power grid;

[0059] When the switch at the common connection point is closed, the park's energy system is connected to the public power grid. The park's energy system can rely on the public power grid's large capacity and reliable transmission capabilities to obtain timely power support when local energy production is insufficient, avoiding production interruptions or equipment shutdowns caused by energy shortages. At the same time, through the flexible adjustment of the park's own distributed energy, it can supply power to the public power grid in reverse during peak load periods, relieving pressure on the public power grid and achieving a two-way balance between energy supply and demand.

[0060] S202, when the current state is closed, acquire multiple parameters to be identified in the park's energy system. These parameters include line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, harmonic attenuation coefficient, and the transformer short-circuit impedance is the short-circuit impedance of the transformer matched with the load equipment.

[0061] S203 inputs the range of line resistance, the range of line inductance, the range of line capacitance, the range of wind power converter capacity, the range of photovoltaic inverter capacity, the range of transformer short-circuit impedance, the range of photovoltaic inverter proportional gain coefficient, the range of photovoltaic inverter integral gain coefficient, the range of wind power converter control parameters, and the range of harmonic attenuation coefficient into the sampling module to obtain multiple parameter combinations output by the sampling module;

[0062] The sampling module takes the ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient as inputs to obtain multiple parameter combinations output by the sampling module, including:

[0063] The ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient are used to form the value data. The value data and sampling instructions are transmitted to the sampling module. The sampling module processes the value data and acquisition instructions to obtain the sampling results. Multiple parameter combinations are obtained from the sampling results.

[0064] Each parameter combination includes a sample value of line resistance, a sample value of line inductance, a sample value of line capacitance, a sample value of wind power converter capacity, a sample value of photovoltaic inverter capacity, a sample value of transformer short-circuit impedance, a sample value of photovoltaic inverter proportional gain coefficient, a sample value of photovoltaic inverter integral gain coefficient, a sample value of wind power converter control parameter, and a sample value of harmonic attenuation coefficient.

[0065] For ease of explanation, the following example is provided:

[0066] For example, there are 5 parameter combinations: parameter combination 1, parameter combination 2, parameter combination 3, parameter combination 4, and parameter combination 5. Parameter combination 1, parameter combination 2, parameter combination 3, parameter combination 4, and parameter combination 5 are different parameter combinations. Parameter combination 1 includes sampled values ​​of the following parameters: line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient.

[0067] Parameter combination 2 includes sampled values ​​of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient.

[0068] Parameter combination 3 includes the sampled values ​​of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient.

[0069] Parameter combination 4 includes sampled values ​​of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient.

[0070] Parameter combination 5 includes the sampled values ​​of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient.

[0071] S204. Input each parameter combination into the simulation model of the park's energy system to obtain the simulation data of each parameter combination. In the simulation data of each parameter combination, obtain the simulation value of the output voltage of the simulation model under each parameter combination, the simulation value of the output current of the simulation model under each parameter combination, the simulation value of the output frequency of the simulation model under each parameter combination, and the simulation value of the total harmonic distortion rate of the simulation model under each parameter combination.

[0072] The process involves inputting each parameter combination into the simulation model of the park's energy system to obtain simulation data for each parameter combination. Within this data, the simulation values ​​for the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination are obtained.

[0073] Obtain the topology data and component parameter information of the park's energy system, input the topology data and component parameter information into the simulation tool, and generate a simulation model of the park's energy system through the simulation tool;

[0074] Each parameter combination is input into the simulation model of the park's energy system to obtain the output results of the simulation model. The simulation data of each parameter combination is obtained from the output results. From the simulation data of each parameter combination, the simulation values ​​of the output voltage, output current, output frequency, and total harmonic distortion of the simulation model under each parameter combination are obtained.

[0075] Acquire the topology data and component parameter information of the park's energy system, input the topology data and component parameter information into the simulation tool, and generate a simulation model of the park's energy system using the simulation tool, including:

[0076] The model of the photovoltaic power generation system, the model of the wind power generation system, the model of the load equipment, and the model of the line are obtained. The model of the photovoltaic power generation system, the model of the wind power generation system, the model of the load equipment, and the model of the line are input into the power system simulation tool. The power system simulation tool processes the model of the photovoltaic power generation system, the model of the wind power generation system, the model of the load equipment, and the model of the line respectively to obtain the simulation unit of the photovoltaic power generation system, the simulation unit of the wind power generation system, the simulation unit of the load equipment, and the simulation unit of the line respectively.

[0077] The system acquires the topology data and component parameter information of the park's energy system, inputs the topology data and component parameter information into the power system simulation tool, and drives the simulation tool to perform connection operations on the simulation units of the photovoltaic power generation system, the wind power generation system, the load equipment, and the line simulation units based on the topology data and component parameter information, thereby generating a simulation model of the park's energy system.

[0078] The models for photovoltaic power generation systems, wind power generation systems, load equipment, and lines can be defined by the user.

[0079] For ease of explanation, the following example is provided:

[0080] For example, the model of a photovoltaic power generation system includes the model of photovoltaic cells and the model of photovoltaic inverters;

[0081] The model for photovoltaic cells is defined as follows:

[0082] ;

[0083] ;

[0084] ;

[0085] This refers to the actual output current of the photovoltaic cell; This is the short-circuit current of the photovoltaic cell; This is the open-circuit voltage; It is the first fitting coefficient; It is the second fitting coefficient; This is the current corresponding to the maximum power point; This is the voltage corresponding to the maximum power point; These are parallel resistors;

[0086] The model of a photovoltaic inverter is defined as follows:

[0087] ;

[0088] This represents the rate of change of the grid-connected current of the photovoltaic inverter along the active axis.

[0089] This represents the rate of change of the grid-connected current of the photovoltaic inverter along the reactive axis.

[0090] This represents the active axis component of the grid-connected current of the photovoltaic inverter;

[0091] This represents the component of the grid-connected current of the photovoltaic inverter on the reactive axis.

[0092] This represents the filter inductance on the output side of the photovoltaic inverter;

[0093] This indicates the DC-side voltage of the photovoltaic inverter;

[0094] This represents the switching coefficient of the active axis of the photovoltaic inverter;

[0095] This represents the switching coefficient of the reactive shaft of the photovoltaic inverter;

[0096] This represents the voltage component of the power grid on the active axis.

[0097] This represents the voltage component of the power grid on the reactive axis.

[0098] This represents the equivalent resistance on the output side of the photovoltaic inverter;

[0099] This represents the angular frequency of the power grid.

[0100] For ease of explanation, the following example is provided:

[0101] For example, models of wind power generation systems, including models of wind turbines and wind power converters;

[0102] The model of a wind turbine is defined as follows:

[0103] ;

[0104] in, This indicates the input power transmitted from the wind turbine to the wind power converter;

[0105] air density; The circular area covered by the rotating rotor of a wind turbine. This is the actual measured wind speed; This represents the wind energy utilization coefficient.

[0106] The model of a wind power converter is defined as follows:

[0107]

[0108] The rate of change of the output power of the wind power converter;

[0109] This refers to the power regulation coefficient of the wind power converter;

[0110] Let be the response constant of the wind power converter;

[0111] This refers to the input power transmitted from the wind turbine generator to the wind power converter.

[0112] This refers to the output power of the wind power converter.

[0113] For ease of explanation, the following example is provided:

[0114] For example, the model of a load device is defined as follows:

[0115] ;

[0116] in, The moment of inertia of the load equipment. The rate of change of motor speed of the load equipment; The driving torque for rotating the load equipment; The rotational speed of the load equipment. The resistance torque of the load equipment itself. This is the damping coefficient of the load equipment.

[0117] For ease of explanation, the following example is provided:

[0118] For example, the model of a circuit is defined as follows:

[0119] ;

[0120] in, This is the fundamental voltage at the first port of the line. This is the fundamental voltage at the second port of the line;

[0121] This refers to the fundamental current at the first port of the line. This is the fundamental current at the second port of the line. For the resistance of the line, For the inductance of the line, The capacitance of the circuit; It is the imaginary unit. This represents the angular frequency of the power grid.

[0122] S205. Based on the simulated values ​​of the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination, and the comprehensive deviation function, a comprehensive deviation is generated for each parameter combination. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system. The park's energy system is then connected to the public power grid based on the target parameter combination. The comprehensive deviation is used to measure the degree of comprehensive deviation of the parameter combination in the four aspects of output voltage, output current, output frequency, and THD.

[0123] Among them, the parameter combination with the smallest comprehensive deviation is selected as the target parameter combination of the park's energy system. The park's energy system is connected to the public power grid according to the target parameter combination. Since the target parameter combination is highly matched, the park's energy system can better adapt to the voltage, frequency and other operating parameters of the public power grid during the grid connection process, thereby effectively reducing various problems caused by parameter mismatch.

[0124] For ease of explanation, the following example is provided:

[0125] For example, the park's energy system includes wind turbines and photovoltaic equipment.

[0126] An unreasonable parameter combination resulted in high harmonic content. These harmonics, injected into the public grid, degrade power quality. The target parameter combination for the park's energy system was selected based on the minimum overall deviation. This target parameter combination, derived from a comprehensive deviation function, enables precise control of output voltage, output current, and output frequency, stabilizing them within specified ranges while keeping the total harmonic distortion (THD) rate extremely low. This effectively reduces the amount of harmonics generated during the operation of the park's energy system, allowing for grid connection between the park's energy system and the public grid. When the park's energy system's own energy production is insufficient, it can promptly obtain power from the public grid to supplement it. Conversely, when the park's energy system has excess energy, it can feed the surplus back to the public grid, achieving bidirectional energy flow and optimized allocation. This enhances the flexibility and reliability of the park's energy system and alleviates the power supply pressure on the public grid.

[0127] The comprehensive deviation function is defined as follows:

[0128] ;

[0129] in, For the first The comprehensive deviation corresponding to the combination of parameters; the first The larger the overall deviation corresponding to each parameter combination, the more likely the simulation model is to be flawed. When all parameters are combined, the greater the overall deviation in output voltage, output current, output frequency, and total harmonic distortion (THD); The smaller the overall deviation corresponding to each parameter combination, the better the simulation model is. When combining these parameters, the smaller the overall deviation in output voltage, output current, output frequency, and total harmonic distortion (THD);

[0130] The simulation model is in the first... Simulated values ​​of output voltage under various parameter combinations;

[0131] This represents the measured output voltage of the park's energy system during grid connection.

[0132] For the simulation model in the first Simulated values ​​of output current under various parameter combinations;

[0133] This represents the measured value of the output current of the park's energy system during grid connection.

[0134] For the simulation model in the first Simulated values ​​of output frequency under various parameter combinations;

[0135] This represents the measured output frequency of the park's energy system during grid connection.

[0136] For the simulation model in the first Simulated values ​​of total harmonic distortion under various parameter combinations;

[0137] This is the measured value of the total harmonic distortion rate of the park's energy system during grid connection.

[0138] For voltage threshold, For current threshold, For frequency threshold, This is the distortion rate threshold; As the first weighting coefficient, This is the second weighting coefficient. This is the third weighting coefficient. It is the fourth weighting coefficient.

[0139] Among them, the output voltage is the voltage of the AC power output by the park's energy system to the public power grid at the point of common coupling; the output current is the current of the AC power output by the park's energy system to the public power grid at the point of common coupling; and the output frequency is the frequency of the AC power output by the park's energy system to the public power grid at the point of common coupling.

[0140] The beneficial effects of this application's embodiments are twofold. Firstly, based on the simulated values ​​of the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination, and the comprehensive deviation function, a comprehensive deviation is generated for each parameter combination. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system. The grid connection between the park's energy system and the public power grid is then completed based on the target parameter combination, which helps improve the efficiency of identifying the target parameter combination for the park's energy system. Secondly, the comprehensive deviation corresponding to the parameter combination... The larger the overall deviation, the greater the comprehensive deviation of the simulation model in terms of output voltage, output current, output frequency, and total harmonic distortion (THD) when using parameter combinations. The smaller the overall deviation of the parameter combinations, the smaller the comprehensive deviation of the simulation model in terms of output voltage, output current, output frequency, and THD when using parameter combinations. Selecting the parameter combination with the smallest overall deviation as the target parameter combination for the park's energy system and completing the grid connection of the park's energy system with the public power grid based on the target parameter combination can ensure that the operating status of the park's energy system connected to the public power grid is highly consistent with the dispatch requirements of the public power grid, reducing the grid connection impact caused by parameter mismatch.

[0141] Please see Figure 3 , Figure 3 The implementation flowchart of S205 provided in the embodiments of this application is described in detail below:

[0142] S301 collects the current signal of the park's energy system through a distributed sensor network, performs harmonic decomposition on the current signal to obtain the effective value of the fundamental component and the effective value of the harmonic component, substitutes the effective value of the fundamental component and the effective value of the harmonic component into the calculation formula of the total harmonic distortion rate to obtain the measured value of the total harmonic distortion rate of the park's energy system.

[0143] S302: Based on the measured value of the total harmonic distortion rate of the park energy system, the simulated value of the output voltage of the simulation model under each parameter combination, the simulated value of the output current of the simulation model under each parameter combination, the simulated value of the output frequency of the simulation model under each parameter combination, the simulated value of the total harmonic distortion rate of the simulation model under each parameter combination, and the comprehensive deviation function, the comprehensive deviation corresponding to each parameter combination is generated. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination of the park energy system, and the target parameter combination is transmitted to the control module of the park energy system.

[0144] S303, the control module obtains the target values ​​of the proportional gain coefficient of the photovoltaic inverter, the integral gain coefficient of the photovoltaic inverter, and the control parameters of the wind power converter from the target parameter combination. It processes the target value of the proportional gain coefficient of the photovoltaic inverter to obtain the first control command, processes the target value of the integral gain coefficient of the photovoltaic inverter to obtain the second control command, and processes the target value of the control parameters of the wind power converter to obtain the third control command. By running the first and second control commands, the photovoltaic inverter in the park's energy system is connected to the public power grid. By running the third control command, the wind power converter in the park's energy system is connected to the public power grid.

[0145] In this embodiment, by running the first control command and the second control command, the photovoltaic inverter in the park energy system is connected to the public power grid. By running the third control command, the wind power converter in the park energy system is connected to the public power grid, which can reduce the grid connection impact of the photovoltaic inverter and the wind power converter.

[0146] For the parameter identification method described in the above embodiments, please refer to [link / reference]. Figure 4 , Figure 4 This is a schematic block diagram of the parameter recognition device provided in the embodiments of this application. Figure 4 The parameter recognition device 400 shown can be applied to, for example... Figure 1The application scenario diagram shows a recognition device. The following section uses a recognition device as an example to illustrate this. Figure 4 The parameter recognition device 400 shown will be described in detail. The parameter recognition device 400 may include a first acquisition module 401, a second acquisition module 402, an input module 403, a third acquisition module 404, and an recognition module 405.

[0147] The first acquisition module 401 is used to acquire the current status of the switch of the common connection point, which is the node that connects the park's energy system to the public power grid;

[0148] The second acquisition module 402 is used to acquire multiple parameters to be identified in the park's energy system when the current state is closed. The multiple parameters to be identified include line resistance, line inductance, line capacitance, capacity of wind power converter, capacity of photovoltaic inverter, transformer short-circuit impedance, proportional gain coefficient of photovoltaic inverter, integral gain coefficient of photovoltaic inverter, control parameters of wind power converter, harmonic attenuation coefficient, and transformer short-circuit impedance is the short-circuit impedance of the transformer matched with the load equipment.

[0149] Input module 403 is used to input the range of line resistance, the range of line inductance, the range of line capacitance, the range of wind power converter capacity, the range of photovoltaic inverter capacity, the range of transformer short-circuit impedance, the range of photovoltaic inverter proportional gain coefficient, the range of photovoltaic inverter integral gain coefficient, the range of wind power converter control parameters, and the range of harmonic attenuation coefficient into the sampling module to obtain multiple parameter combinations output by the sampling module;

[0150] The third acquisition module 404 is used to input each parameter combination into the simulation model of the park energy system to obtain the simulation data of each parameter combination. In the simulation data of each parameter combination, the simulation values ​​of the output voltage, output current, output frequency, and total harmonic distortion of the simulation model under each parameter combination are obtained.

[0151] The identification module 405 is used to generate a comprehensive deviation for each parameter combination based on the simulated values ​​of the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination, and the comprehensive deviation function. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system. The park's energy system is then connected to the public power grid based on the target parameter combination. The comprehensive deviation is used to measure the degree of comprehensive deviation of the parameter combination in four aspects: output voltage, output current, output frequency, and THD.

[0152] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0153] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of the identification device provided in an embodiment of this application.

[0154] like Figure 5 As shown, Figure 5 The identification device 2 includes: at least one processor 20, a memory 21, and a computer program 22 stored in the memory 21 and executable on the at least one processor 20, wherein the processor 20 executes the computer program 22 to implement the steps in any of the above method embodiments.

[0155] The identification device 2 may include, but is not limited to, a processor 20 and a memory 21. Those skilled in the art will understand that... Figure 5 This is merely an example of device 2 and does not constitute a limitation on device 2. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0156] The processor 20 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0157] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A parameter identification method based on a park energy system, characterized in that, An identification device applied to an industrial park energy system, which includes wind turbines equipped with wind power converters, photovoltaic equipment equipped with photovoltaic inverters, and load equipment, wherein the parameter identification method includes: Obtain the current status of the switch at the common connection point, which is the node that connects the park's energy system to the public power grid; When the current state is closed, multiple parameters to be identified in the park's energy system are obtained. These parameters include line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, harmonic attenuation coefficient, and the transformer short-circuit impedance is the short-circuit impedance of the transformer matched with the load equipment. The ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient are input into the sampling module to obtain multiple parameter combinations output by the sampling module. Each parameter combination is input into the simulation model of the park's energy system to obtain simulation data for each parameter combination. From the simulation data of each parameter combination, the simulation values ​​of the output voltage, output current, output frequency, and total harmonic distortion of the simulation model under each parameter combination are obtained. The current signal of the park's energy system is collected by a distributed sensor network. Harmonic decomposition is performed on the current signal to obtain the effective values ​​of the fundamental and harmonic components. These effective values ​​are then substituted into the total harmonic distortion (THD) calculation formula to obtain the measured THD of the park's energy system. Based on the measured THD, simulated output voltage, output current, output frequency, and THD of the simulation model under each parameter combination, and a comprehensive deviation function, a comprehensive deviation is generated for each parameter combination. The parameter combination with the smallest comprehensive deviation is selected as the target parameter combination for the park's energy system, and this target parameter combination is transmitted to the control system of the park's energy system. The control module obtains the target values ​​of the proportional gain coefficient and integral gain coefficient of the photovoltaic inverter and the target values ​​of the control parameters of the wind power converter from the target parameter combination. It processes the target value of the proportional gain coefficient of the photovoltaic inverter to obtain the first control command, processes the target value of the integral gain coefficient of the photovoltaic inverter to obtain the second control command, and processes the target value of the control parameters of the wind power converter to obtain the third control command. By running the first and second control commands, the photovoltaic inverter in the park's energy system is connected to the public power grid. By running the third control command, the wind power converter in the park's energy system is connected to the public power grid. The comprehensive deviation function is used to measure the comprehensive deviation of the parameter combination in four aspects: output voltage, output current, output frequency, and total harmonic distortion rate.

2. The parameter identification method according to claim 1, characterized in that, The ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient are input into the sampling module to obtain multiple parameter combinations output by the sampling module, including: The ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient are used to form the value data. The value data and sampling instructions are transmitted to the sampling module. The sampling module processes the value data and acquisition instructions to obtain the sampling results. Multiple parameter combinations are obtained from the sampling results.

3. The parameter identification method according to claim 1, characterized in that, Each parameter combination is input into the simulation model of the park's energy system to obtain simulation data for each parameter combination. From the simulation data for each parameter combination, the simulated values ​​of the output voltage, output current, output frequency, and total harmonic distortion (THD) of the simulation model under each parameter combination are obtained, including: Obtain the topology data and component parameter information of the park's energy system, input the topology data and component parameter information into the simulation tool, and generate a simulation model of the park's energy system through the simulation tool; Each parameter combination is input into the simulation model of the park's energy system to obtain the output results of the simulation model. The simulation data of each parameter combination is obtained from the output results. From the simulation data of each parameter combination, the simulation values ​​of the output voltage, output current, output frequency, and total harmonic distortion of the simulation model under each parameter combination are obtained.

4. The parameter identification method according to claim 1, characterized in that, The comprehensive deviation function is defined as follows: ； in, For the first The comprehensive deviation corresponding to the combination of parameters; the first The larger the overall deviation corresponding to each parameter combination, the more likely the simulation model is to be flawed. When all parameters are combined, the greater the overall deviation in output voltage, output current, output frequency, and total harmonic distortion (THD); The smaller the overall deviation corresponding to each parameter combination, the better the simulation model is. When combining these parameters, the smaller the overall deviation in output voltage, output current, output frequency, and total harmonic distortion (THD); The simulation model is in the first... Simulated values ​​of output voltage under various parameter combinations; This represents the measured output voltage of the park's energy system during grid connection. For the simulation model in the first Simulated values ​​of output current under various parameter combinations; This represents the measured value of the output current of the park's energy system during grid connection. For the simulation model in the first Simulated values ​​of output frequency under various parameter combinations; This represents the measured output frequency of the park's energy system during grid connection. For the simulation model in the first Simulated values ​​of total harmonic distortion under various parameter combinations; This is the measured value of the total harmonic distortion rate of the park's energy system during grid connection. For voltage threshold, For current threshold, For frequency threshold, This is the distortion rate threshold; As the first weighting coefficient, This is the second weighting coefficient. This is the third weighting coefficient. It is the fourth weighting coefficient.

5. The parameter identification method according to claim 1, characterized in that, Each parameter combination includes a sample value of line resistance, a sample value of line inductance, a sample value of line capacitance, a sample value of wind power converter capacity, a sample value of photovoltaic inverter capacity, a sample value of transformer short-circuit impedance, a sample value of photovoltaic inverter proportional gain coefficient, a sample value of photovoltaic inverter integral gain coefficient, a sample value of wind power converter control parameter, and a sample value of harmonic attenuation coefficient.

6. The parameter identification method according to claim 1, characterized in that, The park's energy system is a comprehensive energy system for green energy parks, which are parks that rely on solar and wind power for power generation.

7. A parameter identification device based on a park energy system, characterized in that, Identification equipment applied to the park's energy system, which includes wind turbines with wind power converters, photovoltaic equipment with photovoltaic inverters, and load equipment, including: The first acquisition module is used to acquire the current status of the switch of the common connection point, which is the node that connects the park's energy system to the public power grid. The second acquisition module is used to acquire multiple parameters to be identified in the park's energy system when the current state is closed. The multiple parameters to be identified include line resistance, line inductance, line capacitance, capacity of wind power converter, capacity of photovoltaic inverter, transformer short-circuit impedance, proportional gain coefficient of photovoltaic inverter, integral gain coefficient of photovoltaic inverter, control parameters of wind power converter, harmonic attenuation coefficient, and transformer short-circuit impedance is the short-circuit impedance of the transformer matched with the load equipment. The input module is used to input the ranges of line resistance, line inductance, line capacitance, wind power converter capacity, photovoltaic inverter capacity, transformer short-circuit impedance, photovoltaic inverter proportional gain coefficient, photovoltaic inverter integral gain coefficient, wind power converter control parameters, and harmonic attenuation coefficient into the sampling module to obtain multiple parameter combinations output by the sampling module; The third acquisition module is used to input each parameter combination into the simulation model of the park's energy system, obtain the simulation data of each parameter combination, and obtain the simulation value of the output voltage, the simulation value of the output current, the simulation value of the output frequency, and the simulation value of the total harmonic distortion rate of the simulation model under each parameter combination from the simulation data of each parameter combination. The identification module is used to collect current signals from the park's energy system through a distributed sensor network, perform harmonic decomposition on the current signals to obtain the effective values ​​of the fundamental and harmonic components, substitute these effective values ​​into the total harmonic distortion (THD) calculation formula to obtain the measured THD of the park's energy system, and generate a comprehensive deviation function based on the measured THD, simulated output voltage, simulated output current, simulated output frequency, and THD of the simulation model under each parameter combination. The module then selects the parameter combination with the smallest comprehensive deviation as the target parameter combination for the park's energy system and transmits the target parameter combination to the park's energy system. The system's control module obtains the target values ​​of the proportional gain coefficient and integral gain coefficient of the photovoltaic inverter and the target values ​​of the control parameters of the wind power converter from the target parameter combination. It processes the target value of the proportional gain coefficient of the photovoltaic inverter to obtain the first control command, processes the target value of the integral gain coefficient of the photovoltaic inverter to obtain the second control command, and processes the target values ​​of the control parameters of the wind power converter to obtain the third control command. By executing the first and second control commands, the photovoltaic inverter in the park's energy system is connected to the public grid. By executing the third control command, the wind power converter in the park's energy system is connected to the public grid. The comprehensive deviation function is used to measure the comprehensive deviation of the parameter combination in four aspects: output voltage, output current, output frequency, and total harmonic distortion rate.

8. An identification device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the parameter identification method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the parameter identification method as described in any one of claims 1 to 6.

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