Power distribution network fault control method and system
By constructing a multi-photovoltaic short-circuit current clustering model and a power direction element sensitivity calculation function, the problem of difficulty in calculating setting values under high-proportion distributed photovoltaic access in traditional distribution network protection methods is solved, realizing accurate fault isolation of distribution network and improving the reliability of protection devices.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-12
- Publication Date
- 2026-03-27
AI Technical Summary
Traditional distribution network protection methods cannot adapt to the nonlinear time-varying characteristics of short-circuit currents caused by high proportions of distributed photovoltaic access, making it difficult to calculate setting values and affecting the accurate isolation of distribution network faults.
A clustering model of multi-photovoltaic short-circuit currents is constructed. By using a quasi-Newton iteration method to characterize the short-circuit current boundary and time difference, combined with the calculation function of the maximum positive and negative offset of the power angle, a power direction element sensitivity calculation function is established to realize accurate calculation of fault current and protection strategy.
It enables precise isolation of distribution network faults under a high proportion of distributed photovoltaic access capacity, and improves the response speed and reliability of protection devices.
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Figure CN121749083A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of active distribution network protection, and more particularly to a method and system for distribution network fault control. Background Technology
[0002] The large-scale integration of distributed photovoltaic (PV) power generation has altered the characteristics of distribution networks, impacting their performance. Traditional distribution networks exhibit linear short-circuit currents with a relatively simple, monotonically decreasing distribution along feeders. Newer distribution networks, however, are affected by the relative positions of distributed power sources, protection systems, and fault points, as well as different fault conditions (variable voltage drops at grid connection points) and time intervals, resulting in nonlinear, time-varying short-circuit currents. When the number and capacity of distributed PV power generation reaches a certain level, traditional distribution automation control technologies become inapplicable, impacting existing relay protection configurations, system short-circuit current levels, distribution automation system functionality, power quality, and on-site operational safety. To mitigate the impact of power system faults, a more suitable protection method for current active distribution networks is needed to achieve precise fault isolation under high-proportion distributed PV capacity, providing a reference for operators to make scientific early warning decisions and emergency response plans. Summary of the Invention
[0003] The purpose of this application is to provide a method and system for controlling distribution network faults, which can achieve precise isolation of distribution network faults under a high proportion of distributed photovoltaic access capacity.
[0004] To achieve the above objectives, the distribution network fault control method provided in this application specifically includes: constructing a multi-PV short-circuit current clustering model based on the structural parameters of the distribution network and the control parameters of the distributed photovoltaic inverters; constructing a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaics based on the multi-PV short-circuit current clustering model by characterizing the short-circuit current boundary using a quasi-Newton iteration method and time difference; establishing a power angle maximum offset calculation function based on the multi-PV short-circuit current clustering model, and constructing a power direction element sensitivity calculation function based on the power angle maximum offset calculation function; and obtaining a distribution network fault control and protection strategy based on the fault current calculation function and the power direction element sensitivity calculation function.
[0005] In some embodiments of this application, constructing a multi-PV short-circuit current clustering model based on the structural parameters of the distribution network and the control parameters of the distributed PV inverter includes: constructing an equivalent voltage source model of the PV power supply based on the control strategy and fault ride-through parameters of the PV inverter; obtaining time-series current data by simulating short-circuit faults under different operating conditions using the equivalent voltage source model; extracting feature data based on the time-series current data; constructing the admittance matrix of the PV nodes using the feature data and the structural parameters of the distribution network; constructing a two-phase interphase short-circuit current calculation model and a three-phase interphase short-circuit current calculation model based on the admittance matrix; and obtaining a multi-PV short-circuit current clustering model based on the two-phase interphase short-circuit current calculation model and the three-phase interphase short-circuit current calculation model.
[0006] In some embodiments of this application, the two-phase interphase short-circuit current calculation model includes:
[0007] ;
[0008] The three-phase interphase short-circuit current calculation model includes:
[0009] ;
[0010] In the above formula, I represents the short-circuit current phasors of the faulted phases B and C during a two-phase short circuit. ABC This is the three-phase short-circuit current. These are the positive-sequence current components and the negative-sequence current components. The current injected into the distributed power source, Z s Z is the equivalent impedance of the system. AB Z BC Z CD These are the impedances of lines AB, BC, and CD, respectively. Let D be the fault impedance when a fault occurs at point D. The voltage of the system is denoted as .
[0011] In some embodiments of this application, constructing a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaic systems includes: characterizing the upper and lower boundary functions of the short-circuit current using a quasi-Newton iteration short-circuit current boundary characterization method based on the multi-photovoltaic short-circuit current clustering model; and constructing a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaic systems by means of time difference based on the upper and lower boundary functions.
[0012] In some embodiments of this application, the upper boundary function includes:
[0013] ;
[0014] The lower boundary function includes:
[0015] ;
[0016] In the above formula, I is the short-circuit current during a two-phase phase-to-phase short circuit. 2A I 2B I 2C This refers to the short-circuit current during a three-phase short circuit. The current injected into the distributed power source, Z s.max Z s.min These are the system's maximum and minimum equivalent impedances, Z. AB Z BC Z CD These are the impedances of lines AB, BC, and CD, respectively. Let D be the fault impedance when a fault occurs at point D. The voltage of the system is denoted as .
[0017] In some embodiments of this application, the fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaic systems includes a first-stage current setting function and a second-stage current setting function.
[0018] The current segment setting function includes:
[0019] ;
[0020] The two-segment current tuning function includes:
[0021] ;
[0022] In the above formula, The reliability coefficient for current segment I is... The reliability coefficient of the current stage II protection is given. , The current injected into the distributed power source, Z s.min These are the minimum equivalent impedances of the system, Z. AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The voltage of the system is denoted as .
[0023] In some embodiments of this application, the function for calculating the maximum positive and negative offset of the power angle based on the multi-photovoltaic short-circuit current clustering model includes:
[0024] The power angle maximum positive offset calculation function includes:
[0025] ;
[0026] The power angle negative maximum offset calculation function includes:
[0027] ;
[0028] In the above formula, α is the rotation factor in the symmetric component method. This represents the positive sequence current component of phase A. , , The current injected into the distributed power source, Z AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The total impedance is... The voltage of the system is denoted as .
[0029] In some embodiments of this application, constructing a power direction element sensitivity calculation function based on the power angle maximum offset calculation function includes: constructing a calculation function for the power direction element sensitivity angle in a two-phase short-circuit model and a three-phase short-circuit model based on the power angle maximum offset calculation function; and obtaining the power direction element sensitivity calculation function based on the calculation function.
[0030] In some embodiments of this application, the power directional element sensitivity calculation function in the two-phase short-circuit model includes:
[0031] ;
[0032] The sensitivity calculation function for power directional elements in the three-phase short-circuit model includes:
[0033] ;
[0034] In the above equation, α is the rotation factor in the symmetric component method. This represents the positive sequence current component of phase A. , , The current injected into the distributed power source, Z AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The total impedance is... The voltage of the system is denoted as .
[0035] This application also provides a distribution network fault control system, the system comprising: a clustering module for constructing a multi-PV short-circuit current clustering model based on the structural parameters of the distribution network and the control parameters of the distributed photovoltaic inverters; a current calculation module for constructing a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaics based on the multi-PV short-circuit current clustering model using a quasi-Newton iteration short-circuit current boundary characterization method and time difference; a sensitivity calculation module for establishing a power angle maximum offset calculation function based on the multi-PV short-circuit current clustering model, and constructing a power direction element sensitivity calculation function based on the power angle maximum offset calculation function; and an analysis module for obtaining a distribution network fault control and protection strategy based on the fault current calculation function and the power direction element sensitivity calculation function.
[0036] This application also provides an electronic 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 above-described method.
[0037] This application also provides a computer-readable storage medium storing a computer program that performs the above-described methods.
[0038] This application also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.
[0039] The beneficial technical effects of this application are as follows: it takes into account the impact of distributed photovoltaic on the short-circuit current at the installation location of the protection device, and compared with other methods, it effectively solves the problem of difficulty in calculating the set value caused by the nonlinear time-varying characteristics of the short-circuit current in the active distribution network, and can achieve accurate isolation of distribution network faults under a high proportion of distributed photovoltaic access capacity. Attached Figure Description
[0040] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, do not constitute a limitation thereof. In the drawings:
[0041] Figure 1 This is a schematic flowchart of a power distribution network fault control method provided in an embodiment of this application;
[0042] Figure 2A This is a schematic diagram illustrating the construction process of a multi-photovoltaic short-circuit current clustering model provided in an embodiment of this application;
[0043] Figure 2B This is a schematic diagram of a multi-photovoltaic power distribution network structure provided in an embodiment of this application;
[0044] Figure 2CThis is a schematic diagram of a multi-photovoltaic short-circuit current clustering set partitioning model provided in an embodiment of this application;
[0045] Figure 3 This is a schematic diagram of the construction process of the fault current calculation function provided in an embodiment of this application;
[0046] Figure 4 This is a schematic diagram illustrating the operating range of the offset angle provided in an embodiment of this application;
[0047] Figure 5 This is a schematic diagram of the process for constructing the power direction element sensitivity calculation function according to an embodiment of this application;
[0048] Figure 6 This is a schematic diagram of the structure of a power distribution network fault control system provided in an embodiment of this application;
[0049] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0050] The following will describe in detail the implementation methods of this application with reference to the accompanying drawings and embodiments, so as to fully understand how this application uses technical means to solve technical problems and achieve technical effects, and to implement it accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in each embodiment of this application can be combined with each other, and the resulting technical solutions are all within the protection scope of this application.
[0051] Furthermore, the steps shown in the flowchart in 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 a different order than that shown here.
[0052] Please refer to Figure 1 As shown, the power distribution network fault control method provided in this application specifically includes:
[0053] S101 constructs a multi-photovoltaic short-circuit current clustering model based on the structural parameters of the distribution network and the control parameters of the distributed photovoltaic inverter;
[0054] S102 Based on the multi-photovoltaic short-circuit current clustering model, a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaics is constructed by characterizing the short-circuit current boundary and time difference through the quasi-Newton iteration short-circuit current boundary characterization method.
[0055] S103 establishes a power angle maximum offset calculation function based on the multi-photovoltaic short-circuit current clustering model, and constructs a power direction element sensitivity calculation function based on the power angle maximum offset calculation function;
[0056] S104 obtains the power distribution network fault control and protection strategy based on the fault current calculation function and the power direction element sensitivity calculation function.
[0057] Specifically, in practical applications, the above-mentioned embodiments mainly involve constructing a multi-PV short-circuit current clustering model to divide the distribution network; based on the multi-PV short-circuit current clustering model, proposing a quasi-Newton iteration method for characterizing short-circuit current boundaries, supplemented by time-level differences, and proposing a fault current calculation method adapted to the nonlinear time-varying characteristics of distributed PV; based on the multi-PV short-circuit current clustering model, establishing a formula for calculating the maximum positive and negative offset of the power angle, and proposing a power direction element sensitivity angle calculation method based on maximum offset balance optimization; and determining the distribution network fault control and protection strategy based on the fault current calculation method for high-proportion distributed PV access and the power direction element sensitivity angle calculation method based on maximum offset balance optimization. Thus, considering the impact of distributed PV on the short-circuit current at the protection device installation location, this method effectively solves the problem of difficulty in calculating setpoints caused by the nonlinear time-varying characteristics of short-circuit current in active distribution networks compared to other methods, enabling accurate fault clearing in distribution networks with high-proportion distributed PV access.
[0058] Please refer to Figure 2A As shown, in some embodiments of this application, constructing a multi-photovoltaic short-circuit current clustering model based on the structural parameters of the distribution network and the control parameters of the distributed photovoltaic inverter includes:
[0059] S201 constructs an equivalent voltage source model of the photovoltaic power supply based on the control strategy and fault ride-through parameters of the photovoltaic inverter;
[0060] S202 simulates short-circuit faults under different operating conditions using the equivalent voltage source model to obtain time-series current data, and extracts feature data based on the time-series current data.
[0061] S203 constructs the admittance matrix of the photovoltaic node using the characteristic data and the structural parameters of the distribution network, and constructs a two-phase interphase short-circuit current calculation model and a three-phase interphase short-circuit current calculation model based on the admittance matrix.
[0062] S204 obtains a multi-photovoltaic short-circuit current clustering model based on the two-phase phase-to-phase short-circuit current calculation model and the three-phase phase-to-phase short-circuit current calculation model.
[0063] In the above embodiments, the two-phase interphase short-circuit current calculation model includes:
[0064] ;
[0065] The three-phase interphase short-circuit current calculation model includes:
[0066] ;
[0067] In the above formula, I represents the short-circuit current phasors of the faulted phases B and C during a two-phase short circuit. ABC This is the three-phase short-circuit current. These are the positive-sequence current components and the negative-sequence current components. The current injected into the distributed power source, Z s Z is the equivalent impedance of the system. AB Z BC Z CD These are the impedances of lines AB, BC, and CD, respectively. Let D be the fault impedance when a fault occurs at point D. The voltage of the system is denoted as .
[0068] Specifically, in practical work, step S101 mainly considers the control strategy and fault ride-through capability of the photovoltaic inverter, and establishes an equivalent voltage source model of the photovoltaic power supply. Short-circuit faults under different operating conditions are simulated using a simulation model to obtain time-series current data. Key features are extracted, and based on the distribution network topology, line parameters, and load distribution, an admittance matrix including photovoltaic nodes is constructed.
[0069] ;
[0070] In the above formula, Y bus Let Y be the admittance matrix. ii Let Y be the autoadmittance of node i. ij Let be the mutual admittance of nodes i and j.
[0071] Subsequently, as Figure 2B As shown, DG1, DG2, and DG3 are photovoltaic units. A three-phase short circuit fault has occurred at this location. To address the occurrence of a two-phase short-circuit fault, a calculation model for the two-phase and three-phase short-circuit currents in a multi-photovoltaic distribution network is constructed. The calculation functions for the two-phase short-circuit current and the three-phase short-circuit current are as shown above.
[0072] Based on the influence of distributed photovoltaic power on the short-circuit current at the installation location of the protection device, you can refer to... Figure 2C As shown, the distribution network is divided into external absorption clusters and auxiliary growth clusters, forming the model basis for characterizing short-circuit current boundaries.
[0073] Please refer to Figure 3 As shown, the fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaic systems includes:
[0074] S301 characterizes the upper and lower boundary functions of the short-circuit current using a quasi-Newton iteration short-circuit current boundary characterization method based on the multi-photovoltaic short-circuit current clustering model.
[0075] S302 constructs a fault current calculation function that adapts to the nonlinear time-varying characteristics of distributed photovoltaic systems by using time step differences based on the upper boundary function and the lower boundary function.
[0076] The upper boundary function includes:
[0077] ;
[0078] The lower boundary function includes:
[0079] ;
[0080] In the above formula, I is the short-circuit current during a two-phase phase-to-phase short circuit. 2A I 2B I 2C This refers to the short-circuit current during a three-phase short circuit. The current injected into the distributed power source, Z s.max Z s.min These are the system's maximum and minimum equivalent impedances, Z. AB Z BC Z CD These are the impedances of lines AB, BC, and CD, respectively. Let D be the fault impedance when a fault occurs at point D. The voltage of the system is denoted as .
[0081] Based on the upper and lower boundaries of the short-circuit current characterized by classification, and considering the nonlinear time-varying characteristics of distributed photovoltaic (PV) systems, a fault current calculation method adapted to the nonlinear time-varying characteristics of distributed PV systems is proposed by combining time level differences.
[0082] In some embodiments of this application, the fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaic systems includes a first-stage current setting function and a second-stage current setting function.
[0083] The current segment setting function includes:
[0084] ;
[0085] The two-segment current tuning function includes:
[0086] ;
[0087] In the above formula, The reliability coefficient for current segment I is... The reliability coefficient of the current stage II protection is given. , The current injected into the distributed power source, Z s.minThese are the minimum equivalent impedances of the system, Z. AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The voltage of the system is denoted as .
[0088] By performing reasonable current stage I and stage II setting calculations, the protection device can operate accurately and quickly when a short-circuit fault occurs, thereby improving the protection performance and reliability of the distribution network.
[0089] Please refer to Figure 4 As shown, in some embodiments of this application, the function for calculating the maximum positive and negative offset of the power angle based on the multi-photovoltaic short-circuit current clustering model includes:
[0090] The power angle maximum positive offset calculation function includes:
[0091] ;
[0092] The power angle negative maximum offset calculation function includes:
[0093] ;
[0094] In the above formula, α is the rotation factor in the symmetric component method. This represents the positive sequence current component of phase A. , , The current injected into the distributed power source, Z AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The total impedance is... The voltage of the system is denoted as .
[0095] Please refer to Figure 5 As shown, in some embodiments of this application, constructing a power direction element sensitivity calculation function based on the power angle maximum offset calculation function includes:
[0096] S501 constructs a calculation function for the sensitivity angle of the power direction element in the two-phase short-circuit model and the three-phase short-circuit model based on the calculation function of the maximum positive and negative offset of the power angle.
[0097] S502 obtains the power direction element sensitivity calculation function based on the calculation function.
[0098] In the above embodiments, the power direction element sensitivity calculation function in the two-phase short-circuit model includes:
[0099] ;
[0100] The sensitivity calculation function for power directional elements in the three-phase short-circuit model includes:
[0101] ;
[0102] In the above equation, α is the rotation factor in the symmetric component method. This represents the positive sequence current component of phase A. , , The current injected into the distributed power source, Z AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The total impedance is... The voltage of the system is denoted as .
[0103] Therefore, based on the above embodiments, the fault control and protection strategy for the distribution network can be determined, and the determination method can adopt the following process:
[0104] In practice, the determination of the distribution network fault control and protection strategy is achieved through the coordinated cooperation of primary side data acquisition and secondary side intelligent setting.
[0105] On the primary side, three-phase voltage transformers and current transformers are deployed at the circuit breaker installation point to collect electrical quantities on both sides in real time, including the amplitude and phase of the three-phase voltage before and after the fault, the short-circuit current direction indication signal, and the real-time operating parameters of the distributed photovoltaic inverter.
[0106] On the secondary side, protection settings are dynamically calculated based on the fault current calculation function: current stage I setting value and current stage II setting value. At the same time, the directional element is optimized based on the power angle offset calculation. By calculating the maximum positive and negative offset of the power angle, the sensitivity angle is dynamically set, and finally, the protection logic of multi-criteria fusion is executed.
[0107] When the measured current exceeds the set value and is in the positive direction, instantaneous tripping occurs; when the measured current exceeds the set value but is in the reverse direction, current protection is blocked. The distribution network fault control and protection strategy is determined through the cooperation of the primary and secondary sides.
[0108] Please refer to Figure 6As shown, this application also provides a distribution network fault control system, the system comprising: a clustering module for constructing a multi-PV short-circuit current clustering model based on the structural parameters of the distribution network and the control parameters of the distributed photovoltaic inverters; a current calculation module for constructing a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaics based on the multi-PV short-circuit current clustering model using a quasi-Newton iteration short-circuit current boundary characterization method and time difference; a sensitivity calculation module for establishing a power angle maximum offset calculation function based on the multi-PV short-circuit current clustering model, and constructing a power direction element sensitivity calculation function based on the power angle maximum offset calculation function; and an analysis module for obtaining a distribution network fault control and protection strategy based on the fault current calculation function and the power direction element sensitivity calculation function.
[0109] Since the principle behind this system's problem-solving approach is similar to that of distribution network fault control methods, the implementation of this system can be found in the implementation of distribution network fault control methods, and the repetitive parts will not be repeated.
[0110] The beneficial technical effects of this application are as follows: it takes into account the impact of distributed photovoltaic on the short-circuit current at the installation location of the protection device, and compared with other methods, it effectively solves the problem of difficulty in calculating the set value caused by the nonlinear time-varying characteristics of the short-circuit current in the active distribution network, and can achieve accurate isolation of distribution network faults under a high proportion of distributed photovoltaic access capacity.
[0111] This application also provides an electronic 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 above-described method.
[0112] This application also provides a computer-readable storage medium storing a computer program that performs the above-described methods.
[0113] This application also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.
[0114] like Figure 7 As shown, the electronic device 600 may also include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily need to include these components. Figure 7 All components shown; in addition, the electronic device 600 may also include Figure 7 For components not shown, please refer to existing technologies.
[0115] like Figure 7As shown, the central processing unit 100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device. The central processing unit 100 receives inputs and controls the operation of various components of the electronic device 600.
[0116] The memory 140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 100 may execute the program stored in the memory 140 to perform information storage or processing, etc.
[0117] Input unit 120 provides input to central processing unit 100. Input unit 120 may be, for example, a keypad or touch input device. Power supply 170 provides power to electronic device 600. Display 160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.
[0118] The memory 140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 140 can also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142 for storing application programs and function programs or processes for executing the operation of the electronic device 600 via the central processing unit 100.
[0119] The memory 140 may also include a data storage unit (data 143) for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit (driver 144) of the memory 140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).
[0120] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processing unit 100 to provide input signals and receive output signals, which can be the same as in a conventional mobile communication terminal.
[0121] Based on different communication technologies, multiple communication modules 110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132, thereby enabling typical telecommunications functions. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. Additionally, the audio processor 130 is coupled to a central processing unit 100, enabling on-device recording via the microphone 132 and on-device playback of stored audio via the speaker 131.
[0122] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0123] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0124] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0125] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0126] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A method for controlling faults in a power distribution network, characterized in that, The method includes: Based on the structural parameters of the distribution network and the control parameters of the distributed photovoltaic inverter, a multi-photovoltaic short-circuit current clustering model is constructed. Based on the multi-photovoltaic short-circuit current clustering model, a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaics is constructed by characterizing the short-circuit current boundary using a quasi-Newton iteration method and time difference. A calculation function for the maximum positive and negative offset of the power angle is established based on the multi-photovoltaic short-circuit current clustering model, and a power direction element sensitivity calculation function is constructed based on the calculation function for the maximum positive and negative offset of the power angle. The fault control and protection strategy for the distribution network is obtained based on the fault current calculation function and the power direction element sensitivity calculation function.
2. The power distribution network fault control method according to claim 1, characterized in that, A multi-PV short-circuit current clustering model is constructed based on the structural parameters of the distribution network and the control parameters of distributed photovoltaic inverters, including: An equivalent voltage source model of the photovoltaic power supply is constructed based on the control strategy and fault ride-through parameters of the photovoltaic inverter. The equivalent voltage source model is used to simulate short-circuit faults under different operating conditions to obtain time-series current data, and feature data is extracted from the time-series current data. The admittance matrix of the photovoltaic node is constructed using the characteristic data and the structural parameters of the distribution network. Based on the admittance matrix, a two-phase interphase short-circuit current calculation model and a three-phase interphase short-circuit current calculation model are constructed respectively. A clustering model for multi-photovoltaic short-circuit currents was obtained based on the calculation models for two-phase and three-phase short-circuit currents.
3. The power distribution network fault control method according to claim 2, characterized in that, The calculation model for the two-phase interphase short-circuit current includes: ； The three-phase interphase short-circuit current calculation model includes: ； In the above formula, I represents the short-circuit current phasors of the faulted phases B and C during a two-phase short circuit. ABC This is the three-phase short-circuit current. These are the positive-sequence current components and the negative-sequence current components. The current injected into the distributed power source, Z s Z is the equivalent impedance of the system. AB Z BC Z CD These are the impedances of lines AB, BC, and CD, respectively. Let D be the fault impedance when a fault occurs at point D. The voltage of the system is denoted as .
4. The power distribution network fault control method according to claim 1, characterized in that, The fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaic systems includes: Based on the multi-photovoltaic short-circuit current clustering model, the upper and lower boundary functions of the short-circuit current are characterized by a quasi-Newton iteration short-circuit current boundary characterization method. Based on the upper boundary function and the lower boundary function, a fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaics is constructed by means of time difference.
5. The power distribution network fault control method according to claim 4, characterized in that, The upper boundary function includes: ； The lower boundary function includes: ； In the above formula, I is the short-circuit current during a two-phase phase-to-phase short circuit. 2A I 2B I 2C This refers to the short-circuit current during a three-phase short circuit. The current injected into the distributed power source, Z s.max Z s.min These are the system's maximum and minimum equivalent impedances, Z. AB Z BC Z CD These are the impedances of lines AB, BC, and CD, respectively. Let D be the fault impedance when a fault occurs at point D. The voltage of the system is denoted as .
6. The power distribution network fault control method according to claim 1, characterized in that, The fault current calculation function adapted to the nonlinear time-varying characteristics of distributed photovoltaic systems includes a first-stage current setting function and a second-stage current setting function. The current segment setting function includes: ； The two-segment current tuning function includes: ； In the above formula, The reliability coefficient for current segment I is... The reliability coefficient of the current stage II protection is given. , The current injected into the distributed power source, Z s.min These are the minimum equivalent impedances of the system, Z. AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The voltage of the system is denoted as .
7. The power distribution network fault control method according to claim 1, characterized in that, The function for calculating the maximum positive and negative offset of the power angle, based on the multi-photovoltaic short-circuit current clustering model, includes: The power angle maximum positive offset calculation function includes: ； The power angle negative maximum offset calculation function includes: ； In the above formula, α is the rotation factor in the symmetric component method. This represents the positive sequence current component of phase A. , , The current injected into the distributed power source, Z AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The total impedance is... The voltage of the system is denoted as .
8. The power distribution network fault control method according to claim 7, characterized in that, The sensitivity calculation function for power direction elements is constructed based on the power angle maximum positive and negative offset calculation function, including: Based on the calculation function of the maximum positive and negative offset of the power angle, a calculation function for the sensitivity angle of the power direction element in the two-phase short-circuit model and the three-phase short-circuit model is constructed. The power direction element sensitivity calculation function is obtained based on the calculation function.
9. The power distribution network fault control method according to claim 8, characterized in that, The sensitivity calculation functions for power directional elements in a two-phase short-circuit model include: ； The sensitivity calculation function for power directional elements in the three-phase short-circuit model includes: ； In the above equation, α is the rotation factor in the symmetric component method. This represents the positive sequence current component of phase A. , , The current injected into the distributed power source, Z AB Z BC Z CD Z DE These are the impedances of lines AB, BC, CD, and DE, respectively. The total impedance is... The voltage of the system is denoted as .
10. A power distribution network fault control system, characterized in that, The system includes: The clustering module is used to construct a multi-photovoltaic short-circuit current clustering model based on the structural parameters of the distribution network and the control parameters of the distributed photovoltaic inverters. The current calculation module is used to construct a fault current calculation function that adapts to the nonlinear time-varying characteristics of distributed photovoltaics by characterizing the short-circuit current boundary and time difference based on the multi-photovoltaic short-circuit current clustering model through the quasi-Newton iteration short-circuit current boundary characterization method. The sensitive calculation module establishes a power angle maximum offset calculation function based on the multi-photovoltaic short-circuit current clustering model, and constructs a power direction element sensitivity calculation function based on the power angle maximum offset calculation function. The analysis module is used to obtain the power distribution network fault control and protection strategy based on the fault current calculation function and the power direction element sensitivity calculation function.
11. An electronic 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 method of any one of claims 1 to 9.
12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.
13. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 9.