Intelligent Power Grid Real-time Fault Location System Based on Power Big Data

Abstract

The present invention discloses an intelligent power grid real-time fault location system based on power big data, which relates to the field of power technology. The system includes: a power grid data acquisition unit for real-time collecting current data and voltage data of each node in the power grid; a power grid model construction unit for constructing a directed graph of the power grid based on each node of the power grid and the connection relationship between each node; a first fault location unit for judging whether there is a fault between two nodes; a second fault location unit for establishing a fault location equation based on the voltage fluctuation equation, the transfer function of frequency response, and the power flow calculation of two nodes, and adding the coordinate position of the fault prediction point and the correction value of the fault position to obtain the actual fault position when the first fault location unit determines that a fault has occurred. The present invention can improve the accuracy and efficiency of fault location, realize fault prediction and correction, and improve the safety and reliability of the operation of the power system.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a smart grid real-time fault location system based on electric power big data. Background Art

[0002] The power system is an indispensable infrastructure in modern society, and its stable operation is crucial to the normal operation of all industries. However, power system failures occur from time to time, such as short circuits and grounding faults, which may cause power outages, equipment damage, and even safety accidents. Therefore, quickly and accurately locating and solving power system failures has become one of the important issues that the power industry needs to solve.

[0003] Traditional power system fault location methods mainly rely on manual inspections and single sensor detection, which have the following problems: Reliance on manual labor: Traditional methods usually require personnel to conduct on-site inspections and troubleshoot, which is time-consuming and labor-intensive, and is easily affected by environmental and human factors, resulting in inaccurate fault location. Single sensor limitation: Traditional methods can usually only collect limited data through a single sensor, which makes it difficult to fully and accurately reflect the operating status of the power system, thus limiting the accuracy and reliability of fault location.

[0004] With the development of big data and artificial intelligence technologies, some smart grid technologies based on big data have emerged, trying to solve the problems of traditional methods: Data collection and analysis: Smart grid technology deploys a large number of sensors and data acquisition equipment to monitor and collect current, voltage and other data at each node of the power system in real time, and uses big data analysis technology to achieve real-time monitoring and analysis of the operating status of the power system. Intelligent fault diagnosis: Based on big data analysis and artificial intelligence algorithms, smart grid technology can quickly diagnose and locate faults in the power system, improving the accuracy and efficiency of fault location.

[0005] Although smart grid technology has brought certain improvements, it still faces the following challenges: Data quality: The amount of data in the power system is huge, but it also faces problems such as low data quality and noise interference. How to effectively process and use big data has become a difficult problem that smart grid technology needs to solve. Fault location accuracy: Although smart grid technology can achieve real-time monitoring and analysis of the power system, in a complex power system environment, the accuracy and precision of fault location still have certain challenges, especially for the diagnosis and location of some hidden faults. Summary of the invention

[0006] In view of this, the present invention provides a smart grid real-time fault location system based on power big data.

[0007] The technical solution adopted by the present invention is as follows:

[0008] Intelligent power grid real-time fault location system based on power big data, the system comprising: a power grid data acquisition unit for real-time acquisition of current data and voltage data of each node in the power grid; a power grid model construction unit for constructing a directed graph of the power grid based on each node of the power grid and the connection relationship between each node, in the directed graph, based on the current data and voltage data of each node collected in real time, establishing a voltage fluctuation equation between any two nodes, and calculating a transfer function of the frequency response between any two nodes; a first fault location unit for determining whether there is a fault between two nodes based on the transfer function of the frequency response between any two nodes and the voltage fluctuation equation; a second fault location unit for establishing a fault location equation based on the voltage fluctuation equation, the transfer function of the frequency response, and the power flow calculation of two nodes, in the case where the first fault location unit determines that a fault has occurred, defining the midpoint position of the two nodes as a fault prediction point, calculating a correction value of the fault location based on the fault location equation, and adding the coordinate position of the fault prediction point and the correction value of the fault location to obtain the position of the actual fault.

[0009] Further, after the power grid data acquisition unit real-time acquires the current data and voltage data of each node in the power grid, it will perform data preprocessing on the acquired current data and voltage data, specifically including: sequentially performing data filtering, data interpolation, and data alignment processing on the acquired current data and voltage data.

[0010] Further, the process of data interpolation specifically includes: the specific process of data filtering includes: passing the current data and voltage data through a high-pass filter; detecting missing data in the current data and voltage data, and filling the missing data by the method of mean interpolation; the process of data alignment specifically includes: performing time alignment processing on the current data and voltage data of different nodes acquired.

[0011] Further, each node of the power grid is connected by a power transmission line; in the directed graph, the power transmission line serves as an edge of the directed graph, describing the connection relationship between each node; the voltage fluctuation equation between two nodes is represented by the following formula:

[0012]

[0013] where represents the influence of thermal effect on voltage fluctuation, where T(x, t) is the temperature at position x at time t, α is the thermal effect coefficient, describing the influence of temperature change on voltage; β·|V(x, t)| 2·V(x, t) represents the normal form correction term, where |V(x, t)| is the modulus of the voltage, β is the correction coefficient used to correct the amplitude effect of the voltage; V(x, t) represents the voltage at position x at time t; L: inductance per unit length; C is the capacitance per unit length; R is the resistance per unit length; α is the thermal effect coefficient, which describes the influence of temperature change on the voltage; β is the correction coefficient.

[0014] Furthermore, the transfer function H(s) of the frequency response is expressed by the following formula:

[0015]

[0016] where K is the transfer function gain; T1 is the time constant of the transfer function; T2 is the damping time constant of the transfer function; A is the thermal effect correction gain; ω0 is the natural frequency of thermal effect correction; B is the normal form correction gain; s is the internal parameter of the transfer function; V(x, s) is the frequency-domain representation of the voltage data; I(x, s) is the frequency-domain representation of the current data.

[0017] Furthermore, for the first fault location unit, the method for determining whether there is a fault between two nodes based on the transfer function of the frequency response and the voltage fluctuation equation of any two nodes specifically includes: calculating the pole position of the transfer function, which corresponds to the resonance frequency; converting the voltage fluctuation equation from the time domain to the frequency domain through Fourier transform to obtain the frequency response of the voltage fluctuation equation, and obtaining its frequency characteristics based on the frequency response of the voltage fluctuation equation; if the resonance frequency corresponding to the extreme point of the transfer function is consistent with the frequency characteristics, then calculate the differences between the amplitude and phase at time t and the amplitude and phase at time t - 1 in the voltage fluctuation equation respectively. If both the difference in amplitude and the difference in phase exceed their respective set thresholds, it is determined that a fault has occurred between the two nodes.

[0018] Furthermore, the fault location equation established by the second fault location unit is expressed by the following formula:

[0019]

[0020] where Δx is the fault location correction value; ΔV is the voltage power flow calculation correction value; Δω is the phase angle power flow calculation correction value.

[0021] Furthermore, the voltage power flow calculation correction value ΔV is calculated by the following formula:

[0022]

[0023] where X dij is the admittance difference between node i and node j among the two nodes; ΔP ij is the difference in active power between node i and node j; z is the imaginary symbol; ΔQij is the difference in reactive power between node i and node j; θ ij is the phase angle difference between node i and node j; Y ij is the average admittance between node i and node j.

[0024] Furthermore, the corrected value Δω of the phase angle power flow calculation is calculated using the following formula:

[0025] Δω = |ω0(Y ij sin(θ ij ) - Y ij cos(θ ij ))|;

[0026] where, || is the modulo operation.

[0027] Adopting the above technical solutions, the present invention has the following beneficial effects: Traditional power system fault location methods rely on manual inspections and single-sensor detections, which are easily affected by human factors and the environment, resulting in inaccurate location results. The intelligent power grid real-time fault location system of the present invention utilizes power big data and advanced analysis algorithms to achieve fast and accurate location of power system faults. By real-time collecting the current data and voltage data of each node in the power grid and combining with power grid model construction and fault location algorithms, the system can accurately locate the fault point, greatly improving the accuracy and efficiency of fault location. The system of the present invention can not only achieve real-time location of faults, but also perform fault prediction and correction. By establishing a fault location equation and predicting the corrected value of the fault point, the system can quickly predict possible fault points after a fault occurs and perform corrections, improving the timeliness and accuracy of fault handling. This fault prediction and correction function can help power system operators take timely measures to reduce the impact of faults on the system and ensure the stable operation of the power system. The power system is an indispensable infrastructure in modern society, and its stable operation is crucial for the normal operation of all walks of life. The intelligent power grid real-time fault location system of the present invention can help power system operators detect and handle faults in a timely manner, improving the operation safety and reliability of the power system. By real-time monitoring the operation status of the power system, detecting potential faults in a timely manner and performing fast location and correction, the impact of faults on the system can be effectively reduced, ensuring the stable operation of the power system and the reliability of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a schematic flow chart of the method for 3D printing modeling design of the bone defect filling body in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] All features disclosed in this specification, or steps in all methods or processes disclosed, may be combined in any manner, except for mutually exclusive features and / or steps.

[0030] Any feature disclosed in this specification (including any appended claims, abstract) may be replaced by other equivalent or similar-purpose alternative features, unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only an example of a series of equivalent or similar features.

[0031] Example 1: Refer to Figure 1 , an intelligent power grid real-time fault location system based on power big data, the system includes: a power grid data acquisition unit for real-time collecting current data and voltage data of each node in the power grid; a power grid model construction unit for constructing a directed graph of the power grid based on each node of the power grid and the connection relationship between each node, in the directed graph, based on the current data and voltage data of each node collected in real time, establishing a voltage fluctuation equation between any two nodes, and calculating the transfer function of the frequency response between any two nodes; a first fault location unit for judging whether there is a fault between two nodes based on the transfer function of the frequency response between any two nodes and the voltage fluctuation equation; a second fault location unit for establishing a fault location equation based on the voltage fluctuation equation, the transfer function of the frequency response, and the power flow calculation of two nodes, in the case where the first fault location unit determines that a fault has occurred, defining the midpoint position of the two nodes as the fault prediction point, calculating the correction value of the fault location based on the fault location equation, and adding the coordinate position of the fault prediction point and the correction value of the fault location to obtain the actual fault location.

[0032] Specifically, the power grid data acquisition unit utilizes advanced sensor technology and is installed at various key nodes of the power grid. These sensors can accurately and quickly measure the current and voltage data at the nodes. For example, for the acquisition of current data, the sensor can measure based on the Hall effect or the principle of current transformers, converting the real-time current value into a digital signal for output. For the acquisition of voltage data, the sensor can measure through the voltage division principle or the capacitance coupling principle, converting the real-time voltage value into a digital signal for output. The acquired current data and voltage data are transmitted to the data processing unit of the system after signal processing and digital conversion. In the data processing unit, these data are integrated, stored, and analyzed and processed through algorithms. Among them, the real-time requirements for current data and voltage data are extremely high. Therefore, during the signal processing process, it is necessary to consider the time delay and accuracy of data transmission to ensure the real-time monitoring of the power grid status by the system. The power grid data acquisition unit also needs to consider the security and reliability of the data. Because the accuracy of power grid data directly affects the performance and reliability of the system. Therefore, during the data acquisition and transmission process, a series of security measures need to be taken, such as data encryption, identity authentication, etc., to prevent data from being maliciously tampered with or stolen, ensuring the accurate monitoring and analysis of the power grid status by the system. The design of the power grid data acquisition unit needs to consider its flexibility and scalability in practical applications. Because the topological structure and operating environment of the power grid may change, the acquisition unit needs to have a certain degree of adaptability and be able to be deployed and adjusted according to needs to meet the data acquisition requirements under different power grid scenarios. The power grid data acquisition unit provides key data support for the real-time fault location system of the smart grid by real-time acquiring current data and voltage data. Based on advanced sensor technology and signal processing technology, as well as the emphasis on data security and reliability, it ensures the accurate monitoring and fault location ability of the system for the power grid status. At the same time, its flexibility and scalability also provide convenience for the application and deployment of the system.

[0033] The power grid model construction unit needs to obtain the topological structure information of the power grid. The topological structure of the power grid describes the connection relationships among various nodes in the power grid, including the electrical connections between nodes and the layout of conductors. Such information can be obtained through power grid design drawings, operation records, or on-site surveys, etc. Through the integration and analysis of this information, a topological structure model of the power grid can be constructed in the form of a directed graph, where nodes represent various devices or nodes in the power grid, and edges represent the connection relationships between nodes. The power grid model construction unit needs to obtain the current and voltage data of power grid nodes. Such data can be obtained in real-time through the power grid data acquisition unit or through historical records. Through the analysis of this data, the real-time states of the current and voltage of each node in the power grid can be determined, thus establishing the state model of the power grid. Based on the topological structure model of the power grid and the current and voltage state information of nodes, the power grid model construction unit can use the basic theories and equations of the power system for modeling and analysis. For example, according to Ohm's law and Kirchhoff's current law, the voltage and current relationships between nodes can be established; according to the power flow equation and power balance equation, the power distribution and power flow conditions of each node in the power grid can be analyzed. Through these equations and models, the operating state of the power grid can be accurately described and analyzed. The power grid model construction unit can also use advanced mathematical methods and computing technologies, such as numerical calculation methods, optimization algorithms, etc., to simulate and analyze the dynamic behavior and stability of the power grid. By simulating the operation of the power grid under different working conditions, the stability and security of the power grid can be evaluated, and references can be provided for the optimization and adjustment of the system. The power grid model construction unit needs to continuously update and optimize the power grid model to adapt to the changes in the power grid operating state and system requirements. This includes regularly updating and correcting the power grid topological structure and node parameters, as well as optimizing and improving the power grid model and algorithms to improve the accuracy and reliability of the system. The power grid model construction unit provides key support for the intelligent power grid real-time fault location system through the modeling and analysis of the power grid structure and operating parameters. Its principle is based on the basic theories and equations of the power system, as well as advanced mathematical methods and computing technologies, ensuring the accurate monitoring and fault location capabilities of the system for the power grid state. At the same time, its continuously updated and optimized characteristics also provide guarantees for the stable operation and performance improvement of the system.

[0034] The first fault location unit calculates the frequency response transfer function between any two nodes by using the current and voltage data of the power grid nodes collected. The frequency response transfer function is a mathematical model that describes the relationship between voltage and current between power grid nodes, and it can reflect the response characteristics of voltage and current between nodes at different frequencies. By analyzing these transfer functions, the electrical connection conditions and power transmission characteristics between nodes can be understood, so as to judge whether there is a fault. The first fault location unit analyzes the voltage fluctuations between nodes by using the voltage fluctuation equation. The voltage fluctuation equation describes the variation law of node voltage in the power grid over time and is an important index for evaluating the stability and fault conditions of the power grid. By monitoring the amplitude and frequency of voltage fluctuations, it can be judged whether there is a fault in the power grid, such as fault types like short circuit and grounding. The first fault location unit comprehensively analyzes the data of the frequency response transfer function and the voltage fluctuation equation, and compares and determines the states between any two nodes in the power grid. By comparing the actual frequency response transfer function with the theoretical model, it can be judged whether the electrical connection between nodes is normal; by comparing the measured voltage fluctuations with the expected range, it can be judged whether there are abnormal conditions between nodes. Through these determinations, it can be initially determined whether there is a fault in the power grid. If the first fault location unit judges the possibility of a fault, it will further analyze the specific location of the fault. In this case, the first fault location unit will take the midpoint position between the fault nodes as the fault prediction point, and calculate the correction value of the fault location according to the frequency response transfer function and the voltage fluctuation equation. This correction value reflects the deviation of the actual fault location relative to the prediction point and can be used to more accurately locate the fault location. Finally, the first fault location unit adds the coordinate position of the fault prediction point and the correction value of the fault location to obtain the actual fault location. This location information can reflect the specific location where the fault occurs and provide an important reference for subsequent fault handling and repair.

[0035] The second fault location unit analyzes the node voltages in the power grid using the voltage fluctuation equation. The voltage fluctuation equation describes the variation law of node voltages in the power grid over time and is an important indicator for evaluating the stability and fault conditions of the power grid. By monitoring the amplitude and frequency of voltage fluctuations, it is possible to preliminarily determine whether there are faults in the power grid. The second fault location unit analyzes the electrical connection conditions between nodes in the power grid using the transfer function of frequency response. The frequency response transfer function can reflect the response characteristics of voltages and currents between nodes at different frequencies, thereby understanding the electrical connection status of nodes in the power grid. By analyzing these transfer functions, it is possible to determine whether the electrical connections between nodes are normal. The second fault location unit evaluates the power flow conditions of each node in the power grid based on the power flow calculation of the nodes. Power flow calculation is a commonly used method in power system analysis for determining parameters such as voltages, powers, and currents of each node in the power grid. By calculating the power flow of the power grid, it is possible to understand the load conditions and power distribution of each node in the power grid, and further determine whether there are faults. If the second fault location unit determines that there is a fault, it will establish a fault location equation. The fault location equation accurately locates the fault position by comprehensively considering the voltage fluctuation equation, the transfer function of frequency response, and the power flow calculation results. In this equation, the correction values of the fault prediction point and the fault position are defined, and the actual fault position is obtained through calculation. The second fault location unit adds the coordinate position of the fault prediction point and the correction value of the fault position to obtain the actual fault position. This position information can reflect the specific location where the fault occurred, providing an important reference for subsequent fault handling and repair.

[0036] Embodiment 2: After the power grid data acquisition unit collects the current data and voltage data of each node in the power grid in real time, it will perform data preprocessing on the collected current data and voltage data, specifically including: sequentially performing data filtering, data interpolation, and data alignment processing on the collected current data and voltage data.

[0037] Specifically, data filtering is a processing step to remove noise and interference in data and retain the effective signals. In the power grid, due to various factors such as electromagnetic interference and equipment operation fluctuations, the collected data may have fluctuations and outliers, affecting the accuracy and reliability of the data. Therefore, the goal of data filtering is to smooth the data curve and remove noise through technologies such as applying digital filters, making the data more stable and reliable. Commonly used filters include moving average filtering, median filtering, band-pass filtering, etc. Appropriate filtering methods are selected for processing according to the characteristics of the data. Data interpolation is to fill in the missing parts of the data to make the data continuous and complete. During the actual collection process, due to equipment failures, communication interruptions, etc., the data collection of some nodes may fail or be missing. To ensure the integrity and continuity of the data, interpolation processing needs to be performed on the missing data. Interpolation methods can be selected according to the characteristics of the data. Common interpolation methods include linear interpolation, polynomial interpolation, Lagrange interpolation, etc. Through these interpolation methods, the possible values of the missing data can be inferred based on the rules and trends of the existing data to fill the gaps in the data. Data alignment processing is to ensure that the data collected by different nodes has the same time standard for subsequent data analysis and comparison. During the actual collection process, the data of different nodes may have time deviations or inconsistencies and need to be aligned. The methods of data alignment processing include timestamp calibration, time series alignment, etc. Through these methods, the data collected by different nodes can be unified to the same time axis to ensure the time series consistency of the data, facilitating subsequent data analysis and processing.

[0038] Embodiment 3: Process the current data and voltage data through a high-pass filter. The high-pass filter can remove the low-frequency components in the data and retain the high-frequency components in the data, thereby filtering out noise and interference and improving the quality and reliability of the data. Next, detect the missing parts in the current data and voltage data, that is, the missing values in the data. Once the missing values are detected, the mean imputation method can be used for filling. The mean imputation method refers to estimating the missing values based on the mean of the existing data or the mean of adjacent data, so that the data remains smooth and continuous at the missing positions. For example, the mean of the data within a certain time range before and after the missing data can be calculated, and then this mean is used to fill the missing value. The purpose of data alignment is to ensure that the current data and voltage data collected by different nodes have the same time standard for facilitating subsequent data analysis and comparison. The specific steps are as follows: Align the current data and voltage data collected by different nodes in terms of time: First, determine the timestamps or sampling time points of the data. Then, sort the data collected by different nodes according to the timestamps or sampling time points. Finally, through methods such as interpolation or truncation, the data collected by different nodes are unified to the same time axis to ensure the time series consistency of the data.

[0039] Example 4: Each node of the power grid is connected by power transmission lines; in a directed graph, the power transmission lines serve as the edges of the directed graph, describing the connection relationships between the nodes; the voltage fluctuation equation between two nodes is expressed by the following formula:

[0040]

[0041] Wherein, represents the influence of thermal effects on voltage fluctuations, where T(x, t) is the temperature at position x at time t, and α is the thermal effect coefficient, describing the influence of temperature changes on voltage; β·|V(x, t)| 2 ·V(x, t) represents the norm correction term, where |V(x, t)| is the modulus of the voltage, and β is the correction coefficient for correcting the amplitude effect of the voltage; V(x, t) represents the voltage at position x at time t; L: inductance per unit length; C is the capacitance per unit length; R is the resistance per unit length; α is the thermal effect coefficient, describing the influence of temperature changes on voltage; β is the correction coefficient.

[0042] Specifically, the first term in the formula represents the second-order spatial partial derivative of the voltage V(x, t) with respect to the position x. This term describes the rate of change of voltage in space, that is, the transverse propagation characteristics of voltage on the transmission line. Through this term, the spatial distribution of voltage on the transmission line can be understood. The second term in the formula describes the influence of the inductance L and capacitance C on the second-order time partial derivative of the voltage V(x, t) at time t. This term reflects the rate of change of voltage with time, that is, the dynamic response characteristics of voltage on the transmission line. Through this term, the rate of change of voltage with time can be understood, that is, the frequency and amplitude of voltage fluctuations. The third term in the formula describes the influence of the resistance R and capacitance C on the first-order time partial derivative of the voltage V(x, t) at time t. This term represents the damping effect of voltage change with time, that is, the process in which voltage fluctuations gradually decay due to the influence of resistance. Through this term, the damping characteristics of voltage fluctuations can be understood, that is, the decay rate and stability of voltage fluctuations. The fourth term in the formula describes the influence of thermal effects on voltage fluctuations. This term considers the Joule heating effect generated by the transmission line passing through current, causing the temperature T(x, t) of the transmission line to change with time t, thereby affecting voltage fluctuations. Among them, α is the thermal effect coefficient, describing the influence of temperature changes on voltage. Through this term, how the temperature change of the transmission line affects voltage fluctuations can be understood, and then the thermal stability and power transmission capacity of the power grid can be evaluated. The last term in the formula β·|V(x, t)| 2·V(x, t) represents the amplitude correction term. This term takes into account the influence of the voltage itself on its fluctuations, that is, the non-linear characteristics of the voltage. Among them, |V(x, t)| is the modulus of the voltage, and β is the correction coefficient used to correct the amplitude effect of the voltage. Through this term, the influence of the non-linear characteristics of the voltage on the voltage fluctuations can be understood, and then the stability and power transmission capacity of the power grid can be evaluated. By solving this wave equation, the characteristics of the voltage fluctuations in the power grid can be evaluated, including frequency, amplitude, and stability, etc. This is of great significance for evaluating the stability and reliability of the power grid, helping to predict the stability of the power grid under different operating conditions, and providing a theoretical basis for the operation and dispatching of the power grid. The voltage fluctuation equation describes the propagation and response characteristics of the voltage between nodes in the power grid and can be used to locate the fault position in the power grid. By analyzing the propagation law of the voltage fluctuations, the voltage change situation around the fault point can be determined, so as to accurately locate the fault position and provide guidance for the fault handling and repair of the power grid. The wave equation can help engineers understand the laws and characteristics of the voltage fluctuations in the power grid and contribute to optimizing the design and planning of the power grid. By analyzing the influence of the voltage fluctuations on each component of the power grid, a more stable and reliable power grid structure can be designed to improve the operation efficiency and power transmission capacity of the power grid. The wave equation can be used as the basic model for power grid simulation and simulation to simulate the voltage fluctuation situation of the power grid under different operating conditions. By solving and simulating the equation, the voltage response of the power grid under different fault conditions can be simulated, the stability and reliability of the power grid can be evaluated, and decision-making support can be provided for the operation and dispatching of the power grid. By analyzing the voltage fluctuation equation, the fault types and causes existing in the power grid can be identified. By analyzing the characteristics and change laws of the voltage fluctuations, the possible fault types in the power grid can be diagnosed, providing guidance for the fault diagnosis and elimination of the power grid.

[0043] Example 5: The transfer function H(s) of the frequency response is expressed by the following formula:

[0044]

[0045] Among them, K is the transfer function gain; T1 is the time constant of the transfer function; T2 is the damping time constant of the transfer function; A is the thermal effect correction gain; ω0 is the natural frequency of the thermal effect correction; B is the normalization correction gain; s is the internal parameter of the transfer function; V(x, s) is the frequency domain representation of the voltage data; I(x, s) is the frequency domain representation of the current data.

[0046] Specifically, the first part in the formula is a first-order inertial link, which describes the basic response characteristics of the system to frequency changes. Where K represents the gain of the transfer function, and T1 represents the time constant of the transfer function. This part mainly reflects the speed of the system's response to frequency changes, that is, the higher the frequency, the smaller the response of the transfer function, and the lower the frequency, the larger the response of the transfer function. This is of great significance for evaluating the frequency response characteristics of the system and can help understand the sensitivity of the system to frequency changes. The second part in the formula is an exponential decay term, which describes the damping characteristics of the system. Where T2 represents the damping time constant of the transfer function. This part mainly reflects the attenuation speed of the system to frequency changes, that is, the higher the frequency, the faster the attenuation of the transfer function, and the lower the frequency, the slower the attenuation of the transfer function. This is of great significance for evaluating the damping characteristics and stability of the system and can help understand the attenuation speed of the system to frequency changes, and then evaluate the stability and reliability of the system. The third part in the formula represents the frequency-domain representation of voltage data, where V(x, s) is the frequency-domain representation of voltage data, is the gain part of the thermal effect correction. This part describes the response characteristics of voltage data in the frequency domain and considers the influence of thermal effects on voltage fluctuations. Where A represents the thermal effect correction gain, and ω0 represents the natural frequency of thermal effect correction. This part can help understand the response of the system to voltage fluctuations at different frequencies and evaluate the influence degree of thermal effects on voltage fluctuations. The last part in the formula represents the frequency-domain representation of current data, where I(x, s) is the frequency-domain representation of current data, is the gain part of the canonical form correction. This part describes the response characteristics of current data in the frequency domain and considers the influence of canonical form correction on current fluctuations. Where B represents the canonical form correction gain. This part can help understand the response of the system to current fluctuations at different frequencies and evaluate the influence degree of canonical form correction on current fluctuations.

[0047] Embodiment 6: The first fault location unit, based on the transfer function of the frequency response of any two nodes and the voltage fluctuation equation, the method for determining whether there is a fault between the two nodes specifically includes: calculating the pole position of the transfer function, and this pole position corresponds to the resonance frequency; converting the voltage fluctuation equation from the time domain to the frequency domain through Fourier transform to obtain the frequency response of the voltage fluctuation equation, and based on the frequency response of the voltage fluctuation equation, obtaining its frequency characteristics; if the resonance frequency corresponding to the extreme point of the transfer function is consistent with the frequency characteristics, then calculate the difference between the amplitude and phase of the voltage fluctuation equation at time t and the amplitude and phase at time t - 1, and if the differences in amplitude and phase both exceed their respective set thresholds, it is determined that a fault has occurred between the two nodes.

[0048] Specifically, by calculating the pole positions of the transfer function, i.e., the resonance frequencies, and analyzing the characteristics of the frequency response, the response of the system to different frequencies can be understood. Faults usually cause abnormal responses of the system at specific frequencies, such as resonance or abnormal attenuation. Therefore, if the resonance frequencies of the transfer function match the characteristics of the frequency response, there may be a fault. At the frequencies where a fault is suspected, by comparing the amplitude and phase differences of the voltage fluctuation equation at different time points, it can be further verified whether there is a fault. Faults usually cause changes in the amplitude and phase of the voltage fluctuation. Therefore, if the difference between the amplitude and phase exceeds the set threshold, there may be a fault. The frequency response refers to the response of the system to input signals of different frequencies. By analyzing the characteristics of the frequency response, the sensitivity of the system to frequency changes, the phase change situation, and the amplitude change situation can be understood. Faults usually cause abnormal responses of the system at specific frequencies, such as resonance or abnormal attenuation. Resonance anomaly means that the amplitude of the system increases abnormally at a certain frequency, which may cause the system to become unstable; while attenuation anomaly means that the amplitude of the system decreases abnormally at a certain frequency, which may cause a decline in the signal transmission quality. The poles of the transfer function are the solutions that make the transfer function zero, i.e., the roots of the denominator of the transfer function being zero. In frequency-domain analysis, these poles correspond to the resonance frequencies of the system. The resonance frequency is the frequency at which the system generates the maximum amplitude in the frequency response, that is, the system has the maximum response to external excitation at this frequency. Therefore, by calculating the pole positions of the transfer function, i.e., the resonance frequencies, the response of the system to different frequencies can be understood. The voltage fluctuation equation describes the variation of voltage with time in the power system. In fault detection, attention is paid to the amplitude and phase of the voltage fluctuation. The amplitude represents the magnitude of the voltage fluctuation, and the phase represents the phase angle of the voltage fluctuation. This information can reflect the characteristics and changes of the voltage fluctuation. At the frequencies where a fault is suspected, by comparing the amplitude and phase of the voltage fluctuation equation at different time points, it is verified whether there is a fault. Usually, normal voltage fluctuations should have stable amplitude and phase. However, when a fault occurs in the system, it may cause changes in the amplitude and phase of the voltage fluctuation. Therefore, if the difference between the amplitude and phase of the voltage fluctuation exceeds the set threshold at the fault frequency, there may be a fault. Faults usually cause changes in system parameters, such as resistance, inductance, etc., thus affecting the amplitude and phase of the voltage fluctuation. When a fault occurs in the system, it may cause abnormal situations such as an increase or decrease in the amplitude of the voltage fluctuation and a shift in the phase. Therefore, by comparing the amplitude and phase differences of the voltage fluctuation equation at different time points, the presence of faults in the system can be indirectly detected.

[0049] Embodiment 7: The fault location equation established by the second fault location unit is represented by the following formula:

[0050]

[0051] Among them, Δx is the fault location correction value; ΔV is the voltage power flow calculation correction value; Δω is the phase angle power flow calculation correction value.

[0052] Specifically, Δx in the formula represents the correction value of the fault location, that is, the correction value obtained through calculation after the first fault location unit determines the fault. And ΔV and Δω respectively represent the correction value of the voltage power flow calculation and the correction value of the phase angle power flow calculation. These values will be used to correct the voltage and phase angle to improve the accuracy of fault location. The remaining parts of the formula include the derivatives of the voltage fluctuation equation and the transfer function, as well as the description of the changes in the voltage fluctuation equation and the phase angle, considering the effects of inductance, capacitance, and resistance. When understanding the principle of the formula, first understand the fault location process in the power system. In the power system, fault location refers to determining the specific location where a fault occurs in the system. This is a crucial task because it directly affects the safety and reliability of the system. Traditional fault location methods usually analyze based on measurement data and models, but this method often requires a large amount of time and resources. Therefore, it is particularly important to use mathematical models and calculation methods to achieve automated fault location. Then, analyze each part of the formula. The first part of the formula describes the derivatives of the voltage fluctuation equation and the transfer function. This part reflects the changes in the power system in the frequency domain and is associated with the frequency characteristics of the system response. By calculating these derivatives, a deeper understanding of the system response can be obtained. And the second part of the formula describes the changes in the voltage fluctuation equation and the phase angle, considering the effects of inductance, capacitance, and resistance. This part is associated with the correction values of the voltage and phase angle and is used to calculate the correction value of the fault location.

[0053] Embodiment 8: The voltage power flow calculation correction value ΔV is calculated using the following formula:

[0054]

[0055] Among them, X dij is the difference in admittance between node i and node j among two nodes; ΔP ij is the difference in active power between node i and node j; z is the imaginary symbol; ΔQ ij is the difference in reactive power between node i and node j; θ ij is the difference in phase angle between node i and node j; Y ij is the average admittance between node i and node j.

[0056] Specifically, ΔV in the formula represents the correction value of voltage flow calculation. In a power system, the stability and accuracy of voltage are one of the important conditions for ensuring the operation of the system. Power flow calculation is used to calculate the relationship between the voltages and powers of each node in the power system to evaluate the stability and operating status of the system. However, due to the complexity and uncertainty of the power system, there may be certain errors in the power flow calculation results. Therefore, correction values are needed to adjust the calculation results to obtain more accurate voltage values. Each term in the formula represents the factors affecting voltage flow calculation. First is X dij , which represents the admittance difference between node i and node j. Admittance is a physical quantity that describes the relationship between voltage and current in a power system, and the admittance difference reflects the difference in voltage and current between nodes. The influence of the admittance difference reflects the voltage fluctuations between different nodes in the system, thus affecting the power flow calculation results. Next, ΔP ij and ΔQ ij respectively represent the active power and reactive power differences between node i and node j. Active power and reactive power are important indicators for transmitting electrical energy in a power system, and their differences can reflect the power change situation in the system. These power differences will affect the voltage stability between nodes, so they need to be considered in the correction value. z is the imaginary symbol used to represent the imaginary part in a complex number. In a power system, complex numbers are often used to describe the phase relationship between voltage and current. The influence of the imaginary part reflects the influence of frequency change on voltage in the power system, so correction is required in voltage flow calculation. θ ij represents the phase angle difference between node i and node j. Phase angle is the phase difference that describes voltage fluctuations in a power system, and it reflects the change in voltage phase between nodes. The change in phase angle will directly affect the voltage stability between nodes, so it also needs to be considered in the correction value. Finally, Y ij represents the average admittance between node i and node j. The average admittance is the average of the admittances between nodes, and it reflects the overall characteristics of voltage and current between nodes. The influence of the average admittance reflects the overall situation of voltage fluctuations between nodes in the system, so correction is required in voltage flow calculation.

[0057] Example 9: The correction value Δω of phase angle power flow calculation is calculated using the following formula:

[0058] Δω = |ω0(Y ij sin(θ ij ) - Y ij cos(θ ij ))|;

[0059] where, || is the modulus operation.

[0060] Specifically, understand each symbol and term in the formula. In the formula, Δω represents the correction value for phase angle power flow calculation, that is, when performing phase angle power flow calculation, the correction value considering the phase angle difference between nodes is taken into account. This correction value is used to adjust the calculation result of the phase angle to obtain a more accurate phase angle value. ω0 represents the natural frequency of the phase angle, reflecting the frequency characteristics of phase change in the system. Y ij represents the average admittance between node i and node j, reflecting the overall characteristics of voltage and current between nodes. θ ij represents the phase angle difference between node i and node j, which is a physical quantity describing the voltage phase difference between nodes in the power system. In the power system, the phase angle is the phase difference describing voltage fluctuations. The change in the phase angle will directly affect the voltage stability and power transmission in the system. Therefore, when performing power flow calculation, it is necessary to consider the phase angle difference between nodes to ensure the accuracy and reliability of the calculation result. The calculation process of the formula involves two main steps. First, calculate Y ij sin(θ ij ) and the difference between Y ij cos(θ ij ), which represents the sine and cosine values of the product of the average admittance between nodes and the phase angle difference. This difference reflects the relationship between the average admittance between nodes and the phase angle difference, and further affects the phase change situation in the system. Next, multiply the difference by the natural frequency ω0 of the phase angle. This step is to calculate the correction value Δω for phase angle power flow calculation. The natural frequency reflects the frequency characteristics of phase change in the system, and multiplying it by the difference can obtain the correction value, which is used to adjust the calculation result of the phase angle. Finally, perform a modulus operation on the calculated correction value, which means taking the absolute value of the correction value. This step ensures that the correction value is a non - negative number, thus ensuring the accuracy and rationality of the correction process.

[0061] The present invention is not limited to the foregoing specific embodiments. The present invention extends to any new feature or any new combination disclosed in this specification, as well as any step of any new method or process disclosed or any new combination.

Claims

1. An intelligent power grid real-time fault location system based on power big data, characterized in that, The system includes: a power grid data acquisition unit for real-time acquisition of current data and voltage data of each node in the power grid; a power grid model construction unit for constructing a directed graph of the power grid based on each node of the power grid and the connection relationship between each node. In the directed graph, based on the current data and voltage data of each node acquired in real time, a voltage fluctuation equation between any two nodes is established, and a transfer function of the frequency response between any two nodes is calculated; a first fault location unit for determining whether there is a fault between two nodes based on the transfer function of the frequency response between any two nodes and the voltage fluctuation equation; a second fault location unit for establishing a fault location equation based on the voltage fluctuation equation, the transfer function of the frequency response, and the power flow calculation of two nodes. When the first fault location unit determines that a fault has occurred, the midpoint position of the two nodes is defined as the fault prediction point. Based on the fault location equation, a correction value of the fault location is calculated, and the coordinate position of the fault prediction point and the correction value of the fault location are added to obtain the actual fault location; each node of the power grid is connected by a power transmission line; in the directed graph, the power transmission line is used as an edge of the directed graph to describe the connection relationship between each node; the voltage fluctuation equation between two nodes is represented by the following formula: ； Among them, represents the influence of thermal effect on voltage fluctuation, where is the position at time of the temperature, is the thermal effect coefficient, which describes the influence of temperature change on voltage; represents the normal form correction term, where is the modulus of voltage, is the correction coefficient used to correct the amplitude effect of voltage; represents the position at time of the voltage; : inductance per unit length; is the capacitance per unit length; is the resistance per unit length; is the thermal effect coefficient, which describes the influence of temperature change on voltage; is the correction coefficient; the transfer function of frequency response is expressed by the following formula: ； Among them, is the gain of the transfer function; is the time constant of the transfer function; is the damping time constant of the transfer function; is the gain of the thermal effect correction; is the natural frequency of the thermal effect correction; is the gain of the normal form correction; is the internal parameter of the transfer function; is the frequency-domain representation of the voltage data; is the frequency-domain representation of the current data; The first fault location unit, based on the transfer function of the frequency response of any two nodes and the voltage fluctuation equation, the method for judging whether there is a fault between the two nodes specifically includes: calculating the pole position of the transfer function, and this pole position corresponds to the resonance frequency; transforming the voltage fluctuation equation from the time domain to the frequency domain through Fourier transform to obtain the frequency response of the voltage fluctuation equation, and based on the frequency response of the voltage fluctuation equation, obtaining its frequency characteristics; if the resonance frequency corresponding to the extreme point of the transfer function is consistent with the frequency characteristics, then calculate the voltage fluctuation equation again at time The difference between the amplitude and phase at time and the amplitude and phase corresponding to the time If the difference in amplitude and the difference in phase both exceed their respective set thresholds, it is determined that a fault has occurred between the two nodes; The fault location equation established by the second fault location unit is represented by the following formula: ； Among them, is the fault location correction value; is the voltage power flow calculation correction value; is the phase angle power flow calculation correction value; The voltage power flow calculation correction value is calculated using the following formula: ； Among them, is the admittance difference between two nodes, node and node ; is the difference in active power between node and node ; is the imaginary symbol; is the difference in reactive power between node and node ; is the phase angle difference between node and node ; is the average admittance between node and node ; The correction value of phase angle power flow calculation is calculated using the following formula: is calculated using the following formula: ; wherein, is a modulo operation.

2. The real-time fault location system for the smart grid based on power big data according to claim 1, characterized in that After the power grid data acquisition unit real-time acquires the current data and voltage data of each node in the power grid, data preprocessing will be performed on the acquired current data and voltage data, specifically including: sequentially performing data filtering, data interpolation, and data alignment processing on the acquired current data and voltage data.

3. The real-time fault location system for smart grid based on power big data according to claim 2, characterized in that, The process of data interpolation specifically includes: The specific process of data filtering includes: passing the current data and voltage data through a high-pass filter; detecting missing data in the current data and voltage data, and filling the missing data by the method of mean interpolation; The process of data alignment specifically includes: performing time alignment processing on the current data and voltage data of different nodes acquired.

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