Fault feature analysis method and system for new energy access power distribution network simulation model

Abstract

The invention discloses a new energy access power distribution network simulation model fault feature analysis method and system, and relates to the technical field of power system engineering, and the method comprises the steps: determining a fault position, and determining a fault type according to the fault position; analyzing current and voltage according to the fault type; simulating the influence of different fault types and fault positions on the power system based on the fault analysis model; and according to a simulation result, proposing isolation strategies of different fault positions. Through real-time monitoring and intelligent analysis, the fault position and type can be quickly and accurately determined, and the accuracy and response speed of fault detection are greatly improved. Based on simulation of the fault analysis model, influences of different fault types and positions on the power system can be simulated, so that a fault processing strategy is optimized; and targeted isolation and recovery measures are taken at different fault positions, so that the flexibility and the high efficiency of the system are ensured, and the reliability and the power supply continuity of the power distribution network are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system engineering, and in particular to a fault characteristic analysis method and system for a distribution network simulation model with new energy access. Background Art

[0002] With the continuous increase in global energy demand and the rapid development of renewable energy, the application of distributed generation (DG) in power systems is becoming more and more widespread. Distributed generation systems can effectively reduce transmission losses and improve power supply reliability by distributing multiple small power generation units close to the load center. In particular, the rapid development of new energy sources such as wind energy and solar energy has provided abundant resources for distributed generation. These new energy technologies are environmentally friendly and renewable, and are gradually replacing traditional fossil energy and becoming an important part of the power system. However, the access of distributed generation systems also brings new challenges, especially in the fault detection and isolation of distribution networks. Traditional distribution network fault handling methods mainly rely on centralized control and manual operation, which is inefficient in the face of complex and changeable distributed power grid environments and is difficult to meet the requirements of rapid response and high reliability. Therefore, it is imperative to develop an active distribution network fault feature analysis method that can effectively detect, analyze and isolate faults.

[0003] Existing fault detection technologies mainly rely on fixed thresholds and simple logical judgments, which are difficult to adapt to complex distributed power grid environments. Traditional methods often take measures only after a fault occurs, with slow response speeds and low accuracy in identifying fault types and locations. In addition, existing fault isolation technologies are mostly based on static preset strategies, lack flexibility, and cannot be dynamically adjusted according to real-time fault conditions, resulting in long power restoration times and affecting power supply reliability. In this context, how to build an efficient, accurate, and intelligent active distribution network fault feature analysis system through advanced simulation and modeling technologies, intelligent sensing and monitoring technologies, and data analysis and machine learning technologies has become a key direction of research and application.

[0004] The present invention proposes a fault characteristic analysis method and system for a simulation model of a distribution network with new energy access, aiming to address the deficiencies in the prior art and provide a more efficient and accurate fault detection and isolation solution. The present invention first determines the fault location and type through real-time monitoring and intelligent analysis, and then simulates the impact of different fault types and locations on the power system based on the fault analysis model. Finally, based on the simulation results, a targeted, flexible and efficient fault isolation strategy is proposed. In particular, for different scenarios where the fault point is upstream, downstream and adjacent lines of DG3, specific response measures are designed, including deploying sensors and monitoring systems, configuring rapid isolation units, using energy storage systems to provide emergency backup power, and establishing a fault response coordination mechanism. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is: how to solve the problem of quickly and accurately detecting, analyzing and isolating faults in an active power distribution network.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a fault characteristic analysis method of a distribution network simulation model for new energy access, which comprises the following steps:

[0008] Determine the fault location and determine the fault type based on the fault location; analyze the current and voltage based on the fault type; simulate the impact of different fault types and fault locations on the power system based on the fault analysis model; and propose isolation strategies for different fault locations based on the simulation results.

[0009] As a preferred solution of the fault characteristic analysis method of the distribution network simulation model for renewable energy access described in the present invention, the determination of the fault location includes the fault point upstream of DG3, the fault point downstream of DG3, and the fault point in the adjacent line.

[0010] As a preferred scheme of the fault characteristic analysis method of the distribution network simulation model for new energy access described in the present invention, wherein: the fault type is determined according to the fault location, including that if the fault point is located at point f1 4 km upstream of DG3 and away from bus 1, the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s.

[0011] If the fault point is located at point f2, 2.2 km downstream of DG3 and 2.2 km from bus 3, the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s.

[0012] If the fault point is located at point f3 of the DG3 adjacent line, which is 2 km away from bus 1, the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s.

[0013] As a preferred scheme of the fault characteristic analysis method of the distribution network simulation model for new energy access described in the present invention, wherein: the analysis of current and voltage according to the fault type includes analyzing the fault current and voltage at the protection CB3 located upstream of DG3 when the transition resistance Rg is 50, 200, and 500 respectively.

[0014] As a preferred solution of the fault characteristic analysis method of the distribution network simulation model of new energy access described in the present invention, the impact on the power system includes setting a single-phase grounding fault, a two-phase short circuit fault, and a three-phase short circuit fault at lines f1, f2, and f3, respectively. If the fault distances of f1, f2, and f3 are 6km, 13.2km, and 8km, respectively, the transition resistance at the fault point is 0.01, and the earth resistivity along the line is 100, there is a coupling relationship between the three-phase fault current traveling waves in the line, and the phase mode transformation technology is used to decouple the three-phase system. By performing the Karen Bell transformation on the current at the measuring end, it can be obtained:

[0015]

[0016] Among them, i a 、i b 、i c are the three-phase currents A, B, and C respectively, i α 、i β 、i γ and i0 are the α-mode component, β-mode component, γ-mode component and 0-mode component of the Karenbauer transform of the phase current, respectively. The 0-mode component propagates between the earth and the three-phase conductors, the α-mode component, β-mode component and γ-mode component only propagate between the conductors, also known as line mode components. The α-mode component propagates simultaneously between the A-phase and B-phase conductors, the β-mode component propagates simultaneously between the A-phase and C-phase conductors, and the γ-mode component propagates simultaneously between the B-phase and C-phase conductors.

[0017] As a preferred scheme of the fault characteristic analysis method of the distribution network simulation model of new energy access described in the present invention, the impact on the power system also includes if a single-phase grounding fault occurs at line f1, f2, and f3 respectively, the transition resistance of the fault point is set to 50Ω, 200Ω, and 500Ω respectively, and the line earth resistivity is 100, and simulation analysis is performed.

[0018] As a preferred solution of the fault characteristic analysis method of the distribution network simulation model for renewable energy access described in the present invention, the isolation strategy includes deploying sensors and monitoring systems when the fault point is upstream of DG3, focusing on abnormal current and voltage changes in the upstream lines, and using machine learning algorithms to analyze the collected data to predict the specific area where the fault occurs. The optimal circuit breaker point is automatically determined based on the real-time data collected from the upstream, allowing the system to self-recover after a short-term fault is cleared, thereby reducing the power supply interruption time.

[0019] When the fault point is downstream of DG3, a fast isolation unit is configured to isolate the fault area when a fault is detected, and an energy storage system is deployed to provide emergency backup power when a fault occurs downstream.

[0020] When the fault point is in the adjacent line, simulation technology is used to regularly detect and maintain the status of the adjacent line, and a fault response coordination mechanism is established, including automatic coordination control and manual intervention adjustment.

[0021] Another object of the present invention is to provide a fault characteristic analysis system for a distribution network simulation model with new energy access, which can solve the problems of inaccurate fault detection, slow response speed and inflexible isolation strategy through real-time monitoring, intelligent analysis and dynamic simulation.

[0022] In order to solve the above technical problems, the present invention provides the following technical solutions: an active distribution network fault characteristic analysis system, comprising a data processing module, a fault detection module, and a simulation and modeling module.

[0023] The data processing module collects sensor data in real time and stores it in a central database to predict the specific area where the fault occurs.

[0024] The fault detection module monitors the changes of current and voltage in real time.

[0025] The simulation and modeling module simulates the impact of faults on the power system based on simulation models of different fault types and fault locations.

[0026] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the fault characteristic analysis method of a distribution network simulation model with new energy access as described above are implemented.

[0027] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for analyzing fault characteristics of a distribution network simulation model for access to new energy as described above.

[0028] Beneficial effects of the present invention: Through real-time monitoring and intelligent analysis, the fault location and type can be quickly and accurately determined, greatly improving the accuracy and response speed of fault detection; based on the simulation of the fault analysis model, the impact of different fault types and locations on the power system can be simulated, thereby optimizing the fault handling strategy; targeted isolation and recovery measures are taken for different fault locations (such as DG3 upstream, downstream and adjacent lines) to ensure the flexibility and efficiency of the system, significantly improving the reliability and power supply continuity of the distribution network. In addition, through machine learning and data analysis technology, potential faults can be predicted in advance, further enhancing the preventive maintenance capabilities of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0030] Figure 1 This is an overall flow chart of a fault characteristic analysis method for a distribution network simulation model with new energy access provided in the first embodiment of the present invention.

[0031] Figure 2 The three-phase short-circuit fault current and voltage diagram at the protection CB3 upstream of DG3 and the downstream protection CB4 in the fault characteristic analysis method of the distribution network simulation model for new energy access provided by the first embodiment of the present invention.

[0032] Figure 3 The two-phase short-circuit fault current and voltage diagram at the protection CB3 upstream of DG3 and the downstream protection CB4 in the fault characteristic analysis method of the distribution network simulation model for new energy access provided by the first embodiment of the present invention.

[0033] Figure 4 Single-phase short-circuit fault current and voltage diagrams at the protection CB3 upstream of DG3 and the protection CB4 downstream of DG3 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0034] Figure 5 The three-phase short-circuit fault current and voltage at the protection CB3 and CB4 downstream of DG3 in the fault characteristic analysis method of the distribution network simulation model for new energy access provided by the first embodiment of the present invention.

[0035] Figure 6 The two-phase short-circuit fault current and voltage at the protection CB3 and CB4 downstream of DG3 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0036] Figure 7 The single-phase short-circuit fault current and voltage at the protection CB3 and CB4 downstream of DG3 in the fault characteristic analysis method of the distribution network simulation model for new energy access provided by the first embodiment of the present invention.

[0037] Figure 8 The three-phase short-circuit fault current and voltage at the protection CB3 and CB4 on both sides of DG3 in the fault characteristic analysis method of the distribution network simulation model for new energy access provided by the first embodiment of the present invention.

[0038] Fig. 9 The two-phase short-circuit fault current and voltage at the protection CB3 and CB4 on both sides of DG3 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0039] Fig.10 The single-phase short-circuit fault current and voltage at the protection CB3 and CB4 on both sides of DG3 in the fault characteristic analysis method of the distribution network simulation model for new energy access provided by the first embodiment of the present invention.

[0040] Fig.11 This is a fault current diagram at the protection CB3 located upstream of DG3 when the transition resistance Rg is 50 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0041] Fig.12 This is a fault voltage diagram at the protection CB3 located upstream of DG3 when the transition resistance Rg is 50 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0042] Fig.13 This is a fault current diagram at the protection CB3 located upstream of DG3 when the transition resistance Rg is 200 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0043] Fig.14 This is a fault voltage diagram at the protection CB3 located upstream of DG3 when the transition resistance Rg is 200 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0044] Fig.15 This is a fault current diagram at the protection CB3 located upstream of DG3 when the transition resistance Rg is 500 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0045] Fig.16This is a fault voltage diagram at the protection CB3 located upstream of DG3 when the transition resistance Rg is 500 in the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0046] Fig.17 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a single-phase grounding fault occurs at point f1 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0047] Fig.18 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a two-phase grounding fault occurs at point f1 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0048] Fig.19 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a three-phase grounding fault occurs at point f1 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0049] Fig. 20 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a single-phase grounding fault occurs at point f2 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0050] Fig.21 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a two-phase grounding fault occurs at point f2 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0051] Fig. 22 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a three-phase grounding fault occurs at point f2 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0052] Fig.23 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a single-phase grounding fault occurs at point f3 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0053] Fig.24 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a two-phase grounding fault occurs at point f3 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0054] Fig.25 This is a diagram of zero-mode and line-mode components of a fault traveling wave when a three-phase grounding fault occurs at point f3 in the fault characteristic analysis method of a distribution network simulation model for renewable energy access provided by the first embodiment of the present invention.

[0055] Fig.26In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the transition resistance of the fault point is 50Ω and the fault point is located upstream of DG3, the zero mode and line mode component diagrams of the fault traveling wave.

[0056] Fig. 27 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the fault point transition resistance is 50Ω and the fault point is located downstream of DG3, the zero mode and line mode component diagrams of the fault traveling wave.

[0057] Fig.28 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the transition resistance of the fault point is 50Ω and the fault point is located in an adjacent line, the zero mode and line mode component diagrams of the fault traveling wave.

[0058] Fig.29 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the fault point transition resistance is 200Ω and the fault point is located upstream of DG3, the zero mode and line mode component diagrams of the fault traveling wave.

[0059] Fig.30 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the fault point transition resistance is 200Ω and the fault point is located downstream of DG3, the zero mode and line mode component diagrams of the fault traveling wave.

[0060] Fig.31 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the transition resistance of the fault point is 200Ω and the fault point is located in the adjacent line of DG3, the zero mode and line mode component diagrams of the fault traveling wave.

[0061] Fig.32 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the fault point transition resistance is 500Ω and the fault point is located upstream of DG3, the zero mode and line mode component diagrams of the fault traveling wave.

[0062] Fig.33 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the fault point transition resistance is 500Ω and the fault point is located downstream of DG3, the zero mode and line mode component diagrams of the fault traveling wave.

[0063] Fig.34 In the fault characteristic analysis method of the distribution network simulation model for renewable energy access provided in the first embodiment of the present invention, when the transition resistance of the fault point is 500Ω and the fault point is located in the adjacent line of DG3, the zero mode and line mode component diagrams of the fault traveling wave. DETAILED DESCRIPTION

[0064] 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.

[0065] Example 1

[0066] Reference Figure 1 to Figure 34 , is an embodiment of the present invention, and provides a fault characteristic analysis method for a distribution network simulation model with new energy access, characterized in that:

[0067] S1: Determine the fault location and the fault type according to the fault location.

[0068] The fault location is determined to include the fault point upstream of DG3, the fault point downstream of DG3, and the fault point in the adjacent line.

[0069] Determine the fault type according to the fault location. If the fault point is located at point f1, 4 km upstream of DG3 and away from bus 1, the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault. The fault time is 0.3s and the fault duration is 0.1s. The fault current and voltage analysis of the protection CB3 upstream of DG3 and the protection CB4 downstream are as follows: Figure 2-Figure 4 shown.

[0070] like Figure 2 As shown in the figure, when a three-phase short circuit fault occurs at point f1 located upstream of the distributed power source, the three-phase current at the upstream protection CB3 of the distributed power source increases, and the three-phase voltage drops sharply to close to 0; the current and voltage at the downstream protection CB4 of the distributed power source both drop significantly and are close to 0.

[0071] like Figure 3 As shown in the figure, when a two-phase (bc) short circuit fault occurs at point f1 located upstream of the distributed generation, the three-phase currents at the upstream protection CB3 of the distributed generation increase, and the fault phase voltage drops sharply; the fault phase current at the downstream protection CB4 of the distributed generation drops sharply, and the fault phase voltage drops sharply.

[0072] like Figure 4 As shown in the figure, when a single-phase (a) grounding fault occurs at point f1 located upstream of the distributed generation, the current of phase A at the upstream protection CB3 of the distributed generation increases, because after the fault, only the distributed generation provides the fault current to CB3, and the fault current provided by DG3 is limited to 2 times the rated current, so the short-circuit current of phase A increases slightly; the fault phase current at the downstream protection CB4 of the distributed generation drops significantly, the current of the non-fault phase increases, and the voltage of the fault phase drops significantly.

[0073] If the fault point is located at point f2 downstream of DG3, 2.2 km from bus 3, and the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s, the fault current and voltage analysis of the protection CB3 and CB4 located downstream of DG3 is as follows: Figure 5-Figure 7 shown.

[0074] like Figure 5 As shown in the figure, when a three-phase short circuit fault occurs at point f2 located downstream of the distributed generation, the fault voltage and current change trends at the upstream protection CB3 of the distributed generation and the downstream protection CB4 are consistent: the three-phase current increases significantly and the three-phase voltage drops sharply.

[0075] like Figure 6 As shown in the figure, when a two-phase (bc) short circuit fault occurs at point f2 located downstream of the distributed generation, the fault voltage and current change trends at the upstream protection CB3 of the distributed generation and the downstream protection CB4 are consistent: the fault phase current increases significantly, the non-fault phase current remains basically unchanged; the fault phase voltage drops sharply.

[0076] like Figure 7 As shown in the figure, when a single-phase (a) ground short circuit fault occurs at point f2 located downstream of the distributed generation, the fault voltage and current change trends at the upstream protection CB3 of the distributed generation and the downstream protection CB4 are consistent: the fault phase current increases significantly, the non-fault phase current amplitude increases, and the three-phase voltage drops sharply to close to 0.

[0077] If the fault point is located at point f3 of the adjacent line of DG3, which is 2 km away from bus 1, and the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s, the fault current and voltage analysis of the protection CB3 and CB4 on both sides of DG3 is as follows: Figure 8-Figure 10 shown.

[0078] like Figure 8 As shown in the figure, when a three-phase short circuit fault occurs at point f3 of the adjacent line of the distributed generation DG3, the fault current and voltage change trends at the upstream protection CB3 and the downstream protection CB4 of the distributed generation are consistent: the fault phase current increases and the fault phase voltage drops.

[0079] like Fig. 9 As shown in the figure, when a two-phase (bc) short circuit fault occurs at point f3 of the adjacent line of the distributed power source DG3, the C-phase current at the upstream protection CB3 of the distributed power source decreases significantly, the B-phase current changes little, and the voltage of the fault phase drops; the fault phase current at the protection CB4 downstream of DG3 decreases, and the voltage of the fault phase drops.

[0080] like Fig.10As shown in the figure, when a single-phase (a) ground short circuit fault occurs at point f3 of the adjacent line of the distributed power source DG3, the fault voltage and current change trends at the upstream protection CB3 of the distributed power source and the downstream protection CB4 are consistent: the fault phase current decreases, the non-fault phase current increases; the fault phase voltage drops sharply.

[0081] S2: Analyze current and voltage according to fault type;

[0082] Analyzing the current and voltage according to the fault type includes analyzing the fault current and voltage at the protection CB3 located upstream of DG3 when the transition resistance Rg is 50, 200, and 500 respectively.

[0083] Specifically, the fault point is located at point f2 downstream of DG3, 2.2 km away from bus 3. A single-phase grounding fault occurs through a transition resistor. The fault time is 0.3s, the fault duration is 0.1s, and the fault current and voltage at the protection CB3 upstream of DG3 are analyzed as follows when the transition resistor Rg is 50, 200, and 500Ω respectively.

[0084] When Rg=50, the fault current is Fig.11 shown.

[0085] When Rg=50, the fault voltage is Fig.12 shown.

[0086] When Rg=200Ω, the fault current is as follows Fig.13 shown.

[0087] When Rg=200Ω, the fault voltage is as follows Fig.14 shown.

[0088] When Rg=500Ω, the fault current is as follows Fig.15 shown.

[0089] When Rg=500Ω, the fault voltage is as follows Fig.13 shown.

[0090] The simulation results show that when a single-phase (a) ground short-circuit fault occurs at point f2 of the downstream line of the distributed power source DG3 through a transition resistor, the larger the transition resistor, the less obvious the change of the fault phase current and the less obvious the voltage drop of the fault phase. When the transition resistor Rg = 500Ω, the fault phase voltage is almost equal to the normal voltage amplitude.

[0091] S3: Simulate the impact of different fault types and fault locations on the power system based on the fault analysis model.

[0092] According to the 10kV distribution network fault simulation model, the traveling wave sampling frequency is 1MHz, the fault occurs after 0.1s, and the wave speed is set to 0.296km / μs. The impact on the power system includes setting single-phase grounding fault, two-phase short circuit fault, and three-phase short circuit fault at lines f1, f2, and f3 respectively. If the fault distances of f1, f2, and f3 are 6km, 13.2km, and 8km respectively, the transition resistance of the fault point is 0.01, and the earth resistivity along the line is 100, there is a coupling relationship between the three-phase fault current traveling waves in the line. The phase mode transformation technology is used to decouple the three-phase system. By performing Karen Bell transformation on the current at the measuring end, it can be obtained:

[0093]

[0094] Among them, i a 、i b 、i c are the three-phase currents A, B, and C respectively, i α 、i β 、i γ and i0 are the α-mode component, β-mode component, γ-mode component and 0-mode component of the Karenbauer transform of the phase current, respectively. The 0-mode component propagates between the earth and the three-phase conductors, the α-mode component, β-mode component and γ-mode component only propagate between the conductors, also known as line mode components. The α-mode component propagates simultaneously between the A-phase and B-phase conductors, the β-mode component propagates simultaneously between the A-phase and C-phase conductors, and the γ-mode component propagates simultaneously between the B-phase and C-phase conductors.

[0095] (1) The fault point is located upstream of DG3.

[0096] When a single-phase grounding fault occurs at point f1 upstream of DG3, the zero-mode and line-mode components of the fault traveling wave are as follows: Fig.17 shown.

[0097] When a two-phase short circuit fault occurs at point f1, the zero mode and line mode components of the fault traveling wave are as follows: Fig.18 shown.

[0098] When a three-phase short circuit fault occurs at point f1, the zero mode and line mode components of the fault traveling wave are as follows: Fig.19 shown.

[0099] (2) The fault point is located downstream of DG3.

[0100] When a single-phase grounding fault occurs at point f2, the zero mode and line mode components of the fault traveling wave are as follows: Fig. 20 shown.

[0101] When a two-phase short circuit fault occurs at point f2, the zero mode and line mode components of the fault traveling wave are as follows: Fig.21 shown.

[0102] When a three-phase short circuit fault occurs at point f2, the zero mode and line mode components of the fault traveling wave are as follows: Fig. 22 shown.

[0103] (3) The fault point is located on the adjacent line.

[0104] When a single-phase grounding fault occurs at point f3, the zero-mode and line-mode components of the fault traveling wave are as follows: Fig.23 shown.

[0105] When a two-phase short circuit fault occurs at point f3, the zero mode and line mode components of the fault traveling wave are as follows: Fig.24 shown.

[0106] When a three-phase short circuit fault occurs at point f3, the zero mode and line mode components of the fault traveling wave are as follows: Fig.25 shown.

[0107] The impact on the power system also includes the simulation analysis if a single-phase grounding fault occurs at line f1, f2, and f3, respectively, and the transition resistance at the fault point is set to 50Ω, 200Ω, and 500Ω, respectively, and the line earth resistivity is 100.

[0108] (1) The transition resistance at the fault point is 50Ω.

[0109] When the fault point is located upstream of DG3, the zero mode and line mode components of the fault traveling wave are as follows: Fig.26 shown.

[0110] The fault point is located downstream of DG3, and the zero mode and line mode components of the fault traveling wave are shown in Figure 27.

[0111] The fault point is located in the adjacent line, and the zero mode and line mode components of the fault traveling wave are as follows: Fig.28 shown.

[0112] (2) The transition resistance at the fault point is 200Ω.

[0113] The fault point is located upstream of DG3. The zero mode and line mode components of the fault traveling wave are as follows: Fig.29 shown.

[0114] The fault point is located downstream of DG3. The zero mode and line mode components of the fault traveling wave are as follows: Fig.30 shown.

[0115] The fault point is located in the adjacent line, and the zero mode and line mode components of the fault traveling wave are as follows: Fig.31 shown.

[0116] (3) The transition resistance at the fault point is 500Ω.

[0117] The fault point is located upstream of DG3. The zero mode and line mode components of the fault traveling wave are as follows: Fig.32 shown.

[0118] The fault point is located downstream of DG3. The zero mode and line mode components of the fault traveling wave are as follows: Fig.33 shown.

[0119] The fault point is located in the adjacent line of DG3. The zero mode and line mode components of the fault traveling wave are as follows: Fig.34 shown.

[0120] S4: Based on the simulation results, isolation strategies for different fault locations are proposed.

[0121] The isolation strategy includes deploying sensors and monitoring systems when the fault point is upstream of DG3, focusing on abnormal current and voltage changes in the downstream lines, using machine learning algorithms to analyze the collected data, predicting the specific area where the fault occurred, and automatically determining the optimal circuit breaker point based on real-time data collected from upstream, allowing the system to self-recover after a short-term fault is cleared, reducing power outage time.

[0122] When the fault point is downstream of DG3, a fast isolation unit is configured to isolate the fault area when a fault is detected, and an energy storage system is deployed to provide emergency backup power when a fault occurs downstream.

[0123] When the fault point is in the adjacent line, simulation technology is used to regularly detect and maintain the status of the adjacent line, and a fault response coordination mechanism is established, including automatic coordination control and manual intervention adjustment.

[0124] In summary, all fault types can generate line mode components, only ground faults can generate zero mode components, and the amplitude of the line mode component of the fault traveling wave will change with the fault location, fault type, and fault point transition resistance. First, when the fault location is fixed, the amplitude of the line mode component will increase with the increase of the fault severity, and will also decrease with the increase of the fault point transition resistance. Then, when the fault type is fixed, the amplitude of the line mode component of the fault traveling wave will decrease with the increase of the distance between the measuring end and the fault location, and will also decrease with the increase of the fault point transition resistance. When the fault transition resistance is fixed, the amplitude of the line mode component of the fault traveling wave will decrease with the increase of the distance between the measuring end and the fault location.

[0125] Example 2

[0126] According to an embodiment of the present invention, there is provided an active power distribution network fault characteristic analysis system, comprising a data processing module, a fault detection module, and a simulation and modeling module.

[0127] The data processing module collects sensor data in real time and stores it in a central database to predict the specific area where the fault occurs.

[0128] The fault detection module monitors the changes of current and voltage in real time.

[0129] The simulation and modeling module simulates the impact of faults on the power system based on simulation models of different fault types and fault locations.

[0130] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0132] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0133] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0134] 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 characteristic analysis method for a distribution network simulation model with new energy access, characterized in that: include: Determine the fault location, and determine the fault type based on the fault location; Analyze current and voltage according to fault type; Simulate the impact of different fault types and fault locations on the power system based on the fault analysis model; Based on the simulation results, isolation strategies for different fault locations are proposed.

2. The method for analyzing fault characteristics of a distribution network simulation model for access to new energy sources as claimed in claim 1, characterized in that: The determination of the fault location includes the fault point being upstream of DG3, the fault point being downstream of DG3, and the fault point being in an adjacent line.

3. The fault characteristic analysis method of the distribution network simulation model of new energy access as claimed in claim 2, characterized in that: The fault type is determined according to the fault location. If the fault point is located at point f1 4 km upstream of DG3 and away from bus 1, the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s. If the fault point is located at point f2 downstream of DG3, 2.2 km from bus 3, the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s; If the fault point is located at point f3 of the DG3 adjacent line, which is 2 km away from bus 1, the fault types are three-phase short circuit, two-phase short circuit and single-phase grounding fault, the fault time is 0.3s, and the fault duration is 0.1s.

4. The method for analyzing fault characteristics of a distribution network simulation model for access to new energy sources as claimed in claim 3, characterized in that: The analyzing of the current and voltage according to the fault type includes analyzing the fault current and voltage at the protection CB3 located upstream of the DG3 when the transition resistance Rg is 50, 200, and 500 respectively.

5. The method for analyzing fault characteristics of a distribution network simulation model for access to new energy sources as claimed in claim 4, characterized in that: The impact on the power system includes setting single-phase grounding fault, two-phase short circuit fault and three-phase short circuit fault at lines f1, f2 and f3 respectively. If the fault distances of f1, f2 and f3 are 6km, 13.2km and 8km respectively, the transition resistance at the fault point is 0.01, and the earth resistivity along the line is 100, there is a coupling relationship between the three-phase fault current traveling waves in the line. The phase mode transformation technology is used to decouple the three-phase system. By performing Karen Bell transformation on the current at the measuring end, it can be obtained: Among them, i a 、i b 、i c are the three-phase currents A, B, and C respectively, i α 、i β 、i γ and i0 are the α-mode component, β-mode component, γ-mode component and 0-mode component of the Karenbauer transform of the phase current, respectively. The 0-mode component propagates between the earth and the three-phase conductors, the α-mode component, β-mode component and γ-mode component only propagate between the conductors, also known as line mode components. The α-mode component propagates simultaneously between the A-phase and B-phase conductors, the β-mode component propagates simultaneously between the A-phase and C-phase conductors, and the γ-mode component propagates simultaneously between the B-phase and C-phase conductors.

6. The method for analyzing fault characteristics of a distribution network simulation model for access to new energy sources as claimed in claim 5, characterized in that: The impact on the power system also includes if single-phase grounding faults occur at lines f1, f2, and f3 respectively, the fault point transition resistance is set to 50Ω, 200Ω, and 500Ω respectively, and the line earth resistivity is 100, and simulation analysis is performed.

7. The method for analyzing fault characteristics of a distribution network simulation model for access to new energy sources as claimed in claim 6, characterized in that: The isolation strategy includes deploying sensors and monitoring systems when the fault point is upstream of DG3, focusing on abnormal current and voltage changes in the downstream line, using machine learning algorithms to analyze the collected data, predicting the specific area where the fault occurred, and automatically determining the best disconnection point based on real-time data collected from the upstream, allowing the system to self-recover after a short-term fault is cleared, reducing the power outage time; When the fault point is downstream of DG3, a fast isolation unit is configured to isolate the fault area when a fault is detected, and an energy storage system is deployed to provide emergency backup power when a fault occurs downstream; When the fault point is in the adjacent line, simulation technology is used to regularly detect and maintain the status of the adjacent line, and a fault response coordination mechanism is established, including automatic coordination control and manual intervention adjustment.

8. A system using the fault characteristic analysis method of the distribution network simulation model of new energy access as claimed in any one of claims 1 to 7, characterized in that: It includes data processing module, fault detection module, simulation and modeling module; The data processing module collects sensor data in real time and stores it in a central database to predict the specific area where the fault occurs; The fault detection module monitors the changes of current and voltage in real time; The simulation and modeling module simulates the impact of faults on the power system based on simulation models of different fault types and fault locations.

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 method for analyzing fault characteristics of a distribution network simulation model for access to new energy sources as 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 method for analyzing fault characteristics of a distribution network simulation model for access to new energy sources as described in any one of claims 1 to 7 are implemented.

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