Fault monitoring method and system based on optical storage direct-flexible hybrid power distribution network

Abstract

The invention discloses a fault monitoring method and system based on an optical storage direct-flexible hybrid power distribution network, and relates to the technical field of power fault monitoring, and the method comprises the following steps: building an equivalent circuit through a direct-current power transmission network, and building a fault circuit model based on the equivalent circuit; collecting a current signal of a direct-current cable of the power distribution network, and carrying out compressed sampling on the current signal to obtain an observation signal; analyzing the observation signal, and judging whether a fault occurs or not according to an analysis result; when a fault occurs, the fault position and the fault resistance are obtained through the fault circuit model. According to the method, the compressed sensing algorithm is combined with the decision tree, the data volume is reduced while key information is reserved, whether a fault exists or not is rapidly recognized through the decision tree model, the real-time performance of power grid state monitoring is effectively improved, and the reliability of the power distribution network is improved; and the defect position and the defect resistance are accurately calculated by adopting an iterative algorithm, and a key basis is provided for troubleshooting.

Description

Technical Field

[0001] The present invention relates to the technical field of power fault monitoring, and in particular to a fault monitoring method and system based on a photovoltaic-storage-direct-flexible hybrid distribution network. Background Art

[0002] The photovoltaic-storage-direct-flexible hybrid distribution network is a new type of building power distribution system that integrates photovoltaic power generation, energy storage, DC power distribution and flexible power consumption technologies. This system can achieve friendly interaction with the power grid, improve the electrification level of building terminals, and is an important way to achieve energy conservation and carbon reduction.

[0003] Rapid detection and removal of DC faults are crucial for the stable operation of flexible DC grids. Since flexible DC grids have low damping characteristics, once a DC side short circuit occurs, the fault current rises very quickly. If the current rise rate cannot be limited and the fault cannot be removed in time, it may cause equipment damage and converter station lockout, affecting power supply reliability. Inter-pole short circuit fault is a very serious fault type in DC transmission systems, and its detection is crucial to ensure the safety and stable operation of the system. Existing hybrid distribution network fault monitoring systems have limitations in real-time, accuracy, and data processing efficiency.

[0004] Short-circuit fault detection in DC power grids is particularly critical, but traditional methods are difficult to locate faults quickly and accurately. The monitoring speed is fast and the accuracy is high. The traveling wave method is mainly based on double-end detection, which requires reliable communication and high sampling accuracy. For example, the document "A DC distribution network cable fault location method based on Prony algorithm" proposes a double-end fault location method, which improves the location accuracy. However, in order to make it, a set of capacitor and inductor positioning modules are added downstream of the circuit breaker, resulting in high costs. The traveling wave method is supplemented by single-end detection. At the beginning of the line, it is necessary to detect the secondary wave of the fault traveling wave. There is a certain difficulty in the existence of the secondary wave. For example, patent application CN111950125A realizes single-end traveling wave DC distribution network fault monitoring and improves the accuracy of wave head recognition. However, it needs to set up double magnetic rings, which has high requirements for equipment. The transient impedance method has low detection cost, but it is slower and less accurate than the traveling wave method. For example, patent application CN116794557A collects real-time voltage through the lock detection point to determine the leakage current to determine the line where the fault point is located, but it cannot accurately locate the fault location. Summary of the invention

[0005] In view of the problems existing in the existing fault monitoring and system based on the photovoltaic-storage-direct-flexible hybrid distribution network, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is that short-circuit fault detection of a DC power grid is relatively difficult and the fault position cannot be accurately located.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a fault monitoring method based on a photovoltaic-storage-direct-flexible hybrid distribution network, which comprises the following steps:

[0009] Establish an equivalent circuit through the DC transmission network, and construct a fault circuit model based on the equivalent circuit;

[0010] Collect the current signal of the DC cable of the distribution network, and perform compression sampling on the current signal to obtain the observation signal;

[0011] Analyze the observed signal and determine whether a fault occurs based on the analysis results;

[0012] When a fault occurs, the fault location and fault resistance are obtained through the fault circuit model.

[0013] As a preferred solution of the fault monitoring method based on the photovoltaic storage direct-flexible hybrid distribution network of the present invention, the fault circuit model is expressed by the formula:

[0014]

[0015] Where I(t) is the current value at time t after the fault occurs, V c It is represented by the voltage across the capacitor before the fault occurs, I L It is represented by the current flowing through the inductor before the fault occurs, L is represented by the total inductance of the DC distribution network, and e at and e bt They are respectively expressed as the decay or increase of current with time;

[0016] Among them: the roots a and b of the characteristic equation are expressed as:

[0017]

[0018] In the formula, q represents the ratio of the distance from the current fault to the relay protection device in the entire DC cable, that is, the fault location, R f is the fault resistance, L c Represents the inductance of the DC cable, R c It is expressed as the resistance of the DC cable, and C is the inter-electrode capacitance of the DC cable.

[0019] As a preferred solution of the fault monitoring method based on the photovoltaic storage direct-flexible hybrid distribution network described in the present invention, the specific steps of obtaining the observation signal include:

[0020] Then install a current sensor on the DC distribution network to collect current signals through sampling frequency;

[0021] The current signal is processed for sparseness and a sparse basis is selected so that the current signal satisfies the formula:

[0022] X = Ψs;

[0023] In the formula, X represents the current signal, Ψ represents the sparse basis, and s represents the sparse coefficient;

[0024] A measurement matrix is ​​randomly generated, and the current signal is projected through the measurement matrix to obtain a compressed observation signal, so that the observation signal satisfies the formula:

[0025] Y = ΦX;

[0026] In the formula, Y represents the observed signal and Φ represents the measurement matrix;

[0027] When the measurement matrix is ​​generated, the correlation coefficient of the measurement matrix is ​​defined as:

[0028]

[0029] in:

[0030]

[0031] Where N is the length of the current signal, M is the length of the observation signal, and It is represented by two related column vectors selected from the measurement matrix, and u(φ) is represented by the correlation coefficient;

[0032] When M<N,

[0033] And the correlation coefficient of the measurement matrix is: Used to filter the measurement matrix.

[0034] As a preferred solution of the fault monitoring method based on the photovoltaic storage direct-flexible hybrid distribution network of the present invention, the step of analyzing the observation signal includes:

[0035] Obtaining historical current signals and corresponding fault results of the DC cable, and establishing a training set with the historical current signals and fault results;

[0036] Randomly sampling samples of the training set, completely randomly dividing the feature points of the training set samples to generate a decision tree group, and combining all decision trees in the decision tree group as a decision tree model;

[0037] Substitute the observed signal into the decision tree model and determine whether there is a fault based on the result;

[0038] The steps of constructing the decision tree group include:

[0039] Sample the training set to generate a feature subset, and randomly extract k features from the feature subset;

[0040] The feature is the standardized kurtosis K, and the standardized kurtosis K of each sample in the feature subset is calculated:

[0041]

[0042] Where y(i) represents the i-th sample value in the observed signal, μ represents the mean value of the observed signal, σ represents the standard deviation of the observed signal, and n represents the number of sample values ​​in the observed signal;

[0043] Randomly select a feature from k features as the first node for segmentation;

[0044] When the first node becomes a leaf node, it is determined whether the decision tree stops growing; when the first node cannot become a leaf node, a new feature is randomly selected as the first node for segmentation;

[0045] If all the feature points of the sub-sample are split, the decision tree stops growing; if not all are split, the decision tree continues to sample feature subsets.

[0046] As a preferred solution of the fault monitoring method based on the photovoltaic storage direct-flexible hybrid distribution network of the present invention, the step of calculating through the fault circuit model includes:

[0047] Set the sampling period T of the sampling device and obtain the latest measured current I(m) and measured voltage V from the sampling device. m ;

[0048] Set t m =T*Q, where t m It is represented as the time point of the mth measurement after the fault occurs, and Q is represented as the number of sampling times after the fault occurs;

[0049] Set I(m) = I(TQ) and obtain the fault location q, fault resistance R through the fault circuit model. f and the sampling times Q, where I(TQ) represents the current obtained by sampling the Qth time when the sampling period is T, the initial fault position q = 0, and the fault resistance R f =0;

[0050] The fault location q and the fault resistance R f Substitute it into the current I(TQ) of the fault circuit model, calculate the number of sampling times Q after the fault occurs, and determine whether Q is an integer. When Q is an integer, the actual fault location q is obtained. z =q, actual fault resistance R fz =R f;

[0051] When Q is not an integer, the fractional part h of the sampling times Q is taken to determine whether the judgment condition h-1<2% is met. If it is met, the actual fault location q is obtained. z =q, actual fault resistance R fz =R f , when it is not satisfied, then determine whether q+Δq≤1 is satisfied;

[0052] If it is satisfied, let q = q + Δq, and substitute it into the current I (TQ) of the fault circuit model for calculation. If it is not satisfied, judge R f +ΔR f ≤25;

[0053] When satisfied, R f =R f +ΔR f , and re-substitute it into the current I(TQ) of the fault circuit model for calculation. If it is not satisfied, the user is prompted that the calculation is wrong, and it is determined whether the user re-measures. If so, re-measure, otherwise, it ends.

[0054] As a preferred solution of the fault monitoring method based on the photovoltaic storage direct-flexible hybrid distribution network of the present invention, wherein: the Δq is 1‰, the ΔR f is 1%.

[0055] As a preferred solution of the fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network described in the present invention, after obtaining the fault location and the fault resistance, they are transmitted to the information database as a historical current signal.

[0056] In a second aspect, an embodiment of the present invention provides a fault monitoring system based on a photovoltaic storage direct-flexible hybrid distribution network, which includes a fault model building module, a sampling module, a compression module, an identification module and a calculation module;

[0057] The fault model establishment module is used to generate an equivalent circuit according to the DC power transmission network, and establish a fault circuit model based on the equivalent circuit.

[0058] The sampling module is used to sample and obtain the current signal of the DC cable of the distribution network;

[0059] The compression module compresses and samples the collected current signal based on a compressed sensing algorithm to obtain an observation signal;

[0060] The identification module is used to analyze the observation signal to determine whether a fault occurs;

[0061] The calculation module is used to calculate the fault location and fault resistance by using an iterative algorithm when a fault occurs.

[0062] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, it implements any step of the above-mentioned fault monitoring method based on a photovoltaic-storage-direct-flexible hybrid distribution network.

[0063] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned fault monitoring method based on a photovoltaic-storage-direct-flexible hybrid distribution network is implemented.

[0064] The beneficial effects of the present invention are as follows: a compressed sensing algorithm is combined with a decision tree to reduce the amount of data while retaining key information, and a decision tree model is used to quickly identify whether a fault exists, thereby effectively improving the real-time performance of power grid status monitoring and improving the reliability of the distribution network; an equivalent circuit model is performed on the DC distribution network fault, and an iterative algorithm is used to accurately calculate the defect location and defect resistance based on the established fault model formula, providing a key basis for troubleshooting. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0066] Figure 1 This is a structural diagram of a hybrid distribution network based on photovoltaic, storage, direct and flexible power generation.

[0067] Figure 2 This is a flow chart of the fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network.

[0068] Figure 3 This is the fault equivalent circuit diagram of the fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network.

[0069] Figure 4 The figure is a flow chart of calculating the fault location of the fault monitoring method based on the hybrid distribution network of photovoltaic energy storage and direct-flexible power generation. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0072] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0073] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0074] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0075] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0076] First of all, Figure 1 This is a structural diagram of a hybrid distribution network based on photovoltaic power generation, energy storage, direct current and flexible power supply. The hybrid distribution network based on photovoltaic power generation, energy storage, direct current and flexible power supply is a new type of building power distribution and utilization system that integrates photovoltaic power generation, energy storage, DC power distribution and flexible power consumption technologies. It can achieve friendly interaction with the power grid and improve the electrification level of building terminals. It is an important way to achieve energy conservation and carbon reduction.

[0077] Inter-pole short-circuit fault is a very serious fault type in DC transmission system, and its detection is crucial to ensure the safety and stable operation of the system. Inter-pole fault can be divided into three stages: capacitor discharge stage, diode free flow stage and grid-side current supply stage. In the capacitor discharge stage, the DC bus capacitor begins to discharge rapidly, causing the system to experience DC voltage collapse. The discharge current has a high peak value and decays over time.

[0078] Example 1

[0079] Reference Figure 2 to Figure 4 , which is the first embodiment of the present invention, and provides a fault monitoring method based on a photovoltaic storage direct-flexible hybrid distribution network, comprising the following steps:

[0080] S1. Establish an equivalent circuit through the DC transmission network, and construct a fault circuit model based on the equivalent circuit.

[0081] according to Figure 3 , the fault circuit model is expressed by the formula:

[0082]

[0083] Where I(t) is the current value at time t after the fault occurs, V c It is represented by the voltage across the capacitor before the fault occurs, I L It is represented by the current flowing through the inductor before the fault occurs, L is represented by the total inductance of the DC distribution network, and e at and e bt They are respectively expressed as the decay or increase of current with time;

[0084] Among them: the roots a and b of the characteristic equation are expressed as:

[0085]

[0086] In the formula, q represents the ratio of the distance from the current fault to the relay protection device in the entire DC cable, that is, the fault location, R f is the fault resistance, L c Represents the inductance of the DC cable, R c It is expressed as the resistance of the DC cable, and C is the inter-electrode capacitance of the DC cable.

[0087] S2. Collect the current signal of the DC cable of the distribution network, and perform compression sampling on the current signal to obtain an observation signal.

[0088] The specific steps to obtain the observed signal include:

[0089] S2.1. Install a current sensor on the DC distribution network and collect current signals through sampling frequency;

[0090] S2.2. Perform sparsity processing on the current signal and select a sparse basis so that the current signal satisfies the formula:

[0091] X = Ψs;

[0092] In the formula, X represents the current signal, Ψ represents the sparse basis, and s represents the sparse coefficient;

[0093] S2.3. Randomly generate a measurement matrix, project the current signal through the measurement matrix, and obtain a compressed observation signal so that the observation signal satisfies the formula:

[0094] Y = ΦX;

[0095] In the formula, Y represents the observed signal and Φ represents the measurement matrix;

[0096] When the measurement matrix is ​​generated, the correlation coefficient of the measurement matrix is ​​defined as:

[0097]

[0098] in:

[0099]

[0100] Where N is the length of the current signal, M is the length of the observation signal, and It is represented by two related column vectors selected from the measurement matrix, and u(φ) is represented by the correlation coefficient;

[0101] When M<N,

[0102] And the correlation coefficient of the measurement matrix is: Used to filter the measurement matrix.

[0103] S3. Analyze the observed signal and determine whether a fault occurs based on the analysis result.

[0104] Decision trees classify or regress data through a series of decision nodes and branches. Each decision node represents a judgment condition on a feature attribute, and the branch represents different judgment results. Finally, each leaf node represents a category or numerical prediction.

[0105] The decision tree swarm algorithm does not need to calculate the information entropy coefficient. It uses standardized kurtosis features and a single feature to divide the decision tree nodes. It generates a decision tree by dividing the nodes through randomly selected features and thresholds, which can save more time.

[0106] The steps for analyzing the observed signal include:

[0107] S3.1. Obtain historical current signals of the DC cable and corresponding fault results, and establish a training set with the historical current signals and fault results;

[0108] S3.2, randomly sampling samples of the training set, completely randomly dividing the feature points of the training set samples to generate a decision tree group, and combining all decision trees in the decision tree group as a decision tree model;

[0109] S3.3, Substitute the observed signal into the decision tree model and determine whether there is a fault based on the result;

[0110] The steps of constructing the decision tree group include:

[0111] Sample the training set to generate a feature subset, and randomly extract k features from the feature subset;

[0112] The feature is the standardized kurtosis K, and the standardized kurtosis K of each sample in the feature subset is calculated:

[0113]

[0114] Where y(i) represents the i-th sample value in the observed signal, μ represents the mean value of the observed signal, σ represents the standard deviation of the observed signal, and n represents the number of sample values ​​in the observed signal;

[0115] Randomly select a feature from k features as the first node for segmentation;

[0116] When the first node becomes a leaf node, it is determined whether the decision tree stops growing; when the first node cannot become a leaf node, a new feature is randomly selected as the first node for segmentation;

[0117] If all the feature points of the sub-sample are split, the decision tree stops growing; if not all are split, the decision tree continues to sample feature subsets.

[0118] S4. When a fault occurs, the fault location and fault resistance are obtained through the fault circuit model.

[0119] like Figure 4 As shown, the steps of calculating through the fault circuit model include:

[0120] Set the sampling period T of the sampling device and obtain the latest measured current I(m) and measured voltage V from the sampling device. m ;

[0121] Set t m =T*Q, where t m It is represented as the time point of the mth measurement after the fault occurs, and Q is represented as the number of sampling times after the fault occurs;

[0122] Set I(m) = I(TQ) and obtain the fault location q, fault resistance R through the fault circuit model. f and the sampling times Q, where I(TQ) represents the current obtained by sampling the Qth time when the sampling period is T, the initial fault position q = 0, and the fault resistance R f =0;

[0123] The fault location q and the fault resistance R f Substitute it into the current I(TQ) of the fault circuit model, calculate the number of sampling times Q after the fault occurs, and determine whether Q is an integer. When Q is an integer, the actual fault location q is obtained. z =q, actual fault resistance R fz =R f ;

[0124] When Q is not an integer, the fractional part h of the sampling times Q is taken to determine whether the judgment condition h-1<2% is met. If it is met, the actual fault location q is obtained. z =q, actual fault resistance R fz =R f , when it is not satisfied, then determine whether q+Δq≤1 is satisfied;

[0125] If it is satisfied, let q = q + Δq, and substitute it into the current I (TQ) of the fault circuit model for calculation. If it is not satisfied, judge R f +ΔR f ≤25;

[0126] When satisfied, R f =R f +ΔR f , and re-substitute it into the current I(TQ) of the fault circuit model for calculation. If it is not satisfied, the user is prompted that the calculation is wrong, and it is determined whether the user re-measures. If so, re-measure, otherwise, it ends.

[0127] The Δq is 1‰, the ΔR f is 1%.

[0128] In the fault circuit model, the DC cable current I(t) after the fault occurs is related to the fault location q and the fault resistance R f The relationship between the change with time is that at time t=0, the current I(0) represents the current value of the DC cable at the time of the fault. When there is a fault in the DC cable, the measured current I(m) is the current value at time t m The corresponding current I(t), the sampling period of the acquisition device measuring the current I(m) is T, then at time t m=QT, where Q is the number of sampling times after the fault occurs. The known quantity: the voltage across the capacitor before the fault occurs V c , the current I flowing through the inductor before the fault occurs L , the total inductance L of the DC distribution network, the sampling period T, the resistance R of the DC cable c , DC cable inductance L c , and the inter-electrode capacitance C of the cable are substituted into the fault circuit model. Then, after the fault occurs, the current I of the DC cable is only related to the fault position q and the fault resistance R f R f It is related to the sampling number Q.

[0129] According to the application scenario of DC cables in hybrid distribution networks, the fault location q represents the percentage of the length from the relay protection device to the fault location in the entire DC cable, with a value of 0-1. The fault resistance R f R f The value range is 0-25Ω.

[0130] Q is a natural number, so the fault position q and the fault resistance R are calculated by iterative algorithm. f R f Substituting the simplified formula, Q can be obtained based on the measured current I, and judging whether Q is an integer or an approximate integer. If it is a near integer, determine the corresponding fault location q and fault resistance R f For actual fault information, the approximate integer can be determined by calculating the absolute value of the difference between the decimal part of Q and 1, and comparing the absolute value with a threshold value, and the threshold value can be 2%.

[0131] After the fault location and the fault resistance are obtained, they are transmitted to an information database as a historical current signal.

[0132] In summary, the compressed sensing algorithm is combined with the decision tree to reduce the amount of data while retaining key information. The decision tree model is used to quickly identify whether there is a fault, which effectively improves the real-time performance of power grid status monitoring and the reliability of the distribution network. The equivalent circuit modeling of the DC distribution network fault is carried out, and the iterative algorithm is used to accurately calculate the defect location and defect resistance based on the established fault model formula, which provides a key basis for troubleshooting.

[0133] Example 2

[0134] On the basis of the first embodiment, this embodiment further provides a fault monitoring system based on a photovoltaic-storage-direct-flexible hybrid distribution network, including a fault model building module, a sampling module, a compression module, an identification module and a calculation module;

[0135] The fault model establishment module is used to generate an equivalent circuit according to the DC power transmission network, and establish a fault circuit model based on the equivalent circuit.

[0136] The sampling module is used to sample and obtain the current signal of the DC cable of the distribution network;

[0137] The compression module compresses and samples the collected current signal based on a compressed sensing algorithm to obtain an observation signal;

[0138] The identification module is used to analyze the observation signal to determine whether a fault occurs;

[0139] The calculation module is used to calculate the fault location and fault resistance by using an iterative algorithm when a fault occurs.

[0140] This embodiment also provides a computer device, which is suitable for the fault monitoring method based on the photovoltaic storage direct-flexible hybrid distribution network, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the fault monitoring method based on the photovoltaic storage direct-flexible hybrid distribution network proposed in the above embodiment.

[0141] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0142] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network proposed in the above embodiment is implemented.

[0143] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0144] Example 3

[0145] On the basis of the previous two embodiments, this embodiment provides a fault monitoring method based on a photovoltaic-storage-direct-flexible hybrid distribution network. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0146] Simulation experiment: Set up different types of fault scenarios, compare the differences between this method and the control example in fault detection speed and accuracy, simulate different network topologies, and test the adaptability of the method.

[0147] Practical application test: Deploy the system in a small-scale PV-storage-DC-flexible hybrid distribution network, collect actual operation data, and compare the fault detection efficiency and accuracy before and after system deployment.

[0148] Comparative example: The fault is located based on the propagation characteristics of the electromagnetic wave generated when the fault occurs on the line.

[0149]

[0150] It can be seen from the above table that fault detection time: this method is significantly faster than the control in all scenarios, on average more than 50% faster; fault location error: the location accuracy of this method is generally higher than that of the control, and the error is controlled within 2%; fault resistance estimation: this method has a smaller error when estimating fault resistance, especially in high-resistance fault scenarios; success rate: the success rate of this method in various fault scenarios is higher than that of the control, especially in complex multi-point faults and high-resistance fault scenarios; adaptability: this method performs well in different types of faults, showing good adaptability.

[0151] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A fault monitoring method based on a photovoltaic-storage-direct-flexible hybrid distribution network, characterized in that: The following steps are included: Establish an equivalent circuit through the DC transmission network, and construct a fault circuit model based on the equivalent circuit; Collect the current signal of the DC cable of the distribution network, and perform compression sampling on the current signal to obtain the observation signal; Analyze the observed signal and determine whether a fault occurs based on the analysis results; When a fault occurs, the fault location and fault resistance are obtained through the fault circuit model.

2. The fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network according to claim 1 is characterized in that: The fault circuit model is expressed by the formula: Where I(t) is the current value at time t after the fault occurs, V c It is represented by the voltage across the capacitor before the fault occurs, I L It is represented by the current flowing through the inductor before the fault occurs, L is represented by the total inductance of the DC distribution network, and e at and e bt They are respectively expressed as the decay or increase of current with time; Where: The roots a and b of the characteristic equation are expressed as: In the formula, q represents the ratio of the distance from the current fault to the relay protection device in the entire DC cable, that is, the fault location, R f is the fault resistance, L c Represents the inductance of the DC cable, R c It is expressed as the resistance of the DC cable, and C is the inter-electrode capacitance of the DC cable.

3. The fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network according to claim 2 is characterized in that: The specific steps to obtain the observed signal include: Then install a current sensor on the DC distribution network to collect current signals through sampling frequency; The current signal is processed for sparseness and a sparse basis is selected so that the current signal satisfies the formula: X = Ψs; In the formula, X represents the current signal, Ψ represents the sparse basis, and s represents the sparse coefficient; A measurement matrix is ​​randomly generated, and the current signal is projected through the measurement matrix to obtain a compressed observation signal, so that the observation signal satisfies the formula: Y = ΦX; In the formula, Y represents the observed signal and Φ represents the measurement matrix; When the measurement matrix is ​​generated, the correlation coefficient of the measurement matrix is ​​defined as: in: Where N is the length of the current signal, M is the length of the observation signal, and It is represented by two related column vectors selected from the measurement matrix, and u(φ) is represented by the correlation coefficient; When M<N, And the correlation coefficient of the measurement matrix is: Used to filter the measurement matrix.

4. The fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network according to claim 3 is characterized in that: The steps for analyzing the observed signal include: Obtaining historical current signals and corresponding fault results of the DC cable, and establishing a training set with the historical current signals and fault results; Randomly sampling samples of the training set, completely randomly dividing the feature points of the training set samples to generate a decision tree group, and combining all decision trees in the decision tree group as a decision tree model; Substitute the observed signal into the decision tree model and determine whether there is a fault based on the result; The steps of constructing the decision tree group include: Sample the training set to generate a feature subset, and randomly extract k features from the feature subset; The feature is the standardized kurtosis K, and the standardized kurtosis K of each sample in the feature subset is calculated: Where y(i) represents the i-th sample value in the observed signal, μ represents the mean value of the observed signal, σ represents the standard deviation of the observed signal, and n represents the number of sample values ​​in the observed signal; Randomly select a feature from k features as the first node for segmentation; When the first node becomes a leaf node, it is determined whether the decision tree stops growing; when the first node cannot become a leaf node, a new feature is randomly selected as the first node for segmentation; If all the feature points of the sub-sample are split, the decision tree stops growing; if not all are split, the decision tree continues to sample feature subsets.

5. The fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network according to claim 4 is characterized in that: The steps of calculating through the fault circuit model include, Set the sampling period T of the sampling device and obtain the latest measured current I(m) and measured voltage V from the sampling device. m ; Set t m =T*Q, where t m It is represented as the time point of the mth measurement after the fault occurs, and Q is represented as the number of sampling times after the fault occurs; Set I(m) = I(TQ) and obtain the fault location q, fault resistance R through the fault circuit model. f and the sampling times Q, where I(TQ) represents the current obtained by sampling the Qth time when the sampling period is T, the initial fault position q = 0, and the fault resistance R f =0; The fault location q and the fault resistance R f Substitute it into the current I(TQ) of the fault circuit model, calculate the number of sampling times Q after the fault occurs, and determine whether Q is an integer. When Q is an integer, the actual fault location q is obtained. z =q, actual fault resistance R fz =R f ; When Q is not an integer, the fractional part h of the sampling times Q is taken to determine whether the judgment condition h-1<2% is met. If it is met, the actual fault location q is obtained. z =q, actual fault resistance R fz =R f , when it is not satisfied, then determine whether q+Δq≤1 is satisfied; If it is satisfied, let q = q + Δq, and substitute it into the current I (TQ) of the fault circuit model for calculation. If it is not satisfied, judge R f +ΔR f ≤25; When satisfied, R f =R f +ΔR f , and re-substitute it into the current I(TQ) of the fault circuit model for calculation. If it is not satisfied, the user is prompted that the calculation is wrong, and it is determined whether the user re-measures. If so, re-measure, otherwise, it ends.

6. The fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network according to claim 5 is characterized in that: The Δq is 1‰, the ΔR f is 1%.

7. The fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network according to claim 6 is characterized in that: After the fault location and the fault resistance are obtained, they are transmitted to an information database as a historical current signal.

8. A fault monitoring system based on a hybrid distribution network of photovoltaic, storage, direct current and flexible power supply, based on the fault monitoring method based on a hybrid distribution network of photovoltaic, storage, direct current and flexible power supply according to any one of claims 1 to 7, characterized in that: It includes a fault model building module, a sampling module, a compression module, an identification module and a calculation module; The fault model establishment module is used to generate an equivalent circuit according to the DC power transmission network, and establish a fault circuit model based on the equivalent circuit. The sampling module is used to sample and obtain the current signal of the DC cable of the distribution network; The compression module compresses and samples the collected current signal based on a compressed sensing algorithm to obtain an observation signal; The identification module is used to analyze the observation signal to determine whether a fault occurs; The calculation module is used to calculate the fault location and fault resistance by using an iterative algorithm when a fault occurs.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the fault monitoring method based on the photovoltaic-storage-direct-flexible hybrid distribution network described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the fault monitoring method based on a photovoltaic-storage-direct-flexible hybrid distribution network described in any one of claims 1 to 7 are implemented.

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