Fault self-healing power restoration method and device for power distribution network

Abstract

The invention discloses a power distribution network fault self-healing power restoration method and device, and belongs to the technical field of power distribution networks. Obtaining fault data corresponding to a plurality of fault types, performing fault simulation in the mathematical model of the power distribution network, and determining a self-healing power restoration operation rule; acquiring operation data of the power distribution network in real time, determining a current fault type of the power distribution network, and determining equipment action constant values and equipment action sequences corresponding to the plurality of protection equipment in the self-healing power restoration operation rule; when the operation data of the power distribution network reaches the equipment action constant value, performing isolation processing on each protection equipment according to the equipment action sequence, and collecting the isolated operation data of the power distribution network, thereby determining a fault area and a non-fault area of the power distribution network; and removing the fault area, and forwarding the non-fault area. Therefore, by implementing the method, the problem of low self-healing power restoration efficiency of the power distribution network in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution networks, and in particular to a method and device for self-healing power restoration of a power distribution network fault. Background Art

[0002] Distribution network self-healing technology, a key means of improving power supply reliability, is gaining increasing attention in practical applications. It typically uses feeder groups or automated network connectivity to rapidly restore power after a distribution network failure. However, current distribution network self-healing technology still has some issues and shortcomings, hindering further improvement in its effectiveness.

[0003] Existing self-healing configuration strategies and operating rules use unified standards and models, failing to consider the actual characteristics and operating conditions of distribution networks in different regions. This makes them difficult to adapt to the complex and ever-changing distribution network environment. Furthermore, the switching settings of various devices in the distribution network do not take into account the real-time status of the devices. This can lead to inaccurate setting execution due to factors such as device aging, reducing the efficiency of distribution network self-healing and thus affecting the reliability of the distribution network. Summary of the Invention

[0004] The present invention provides a method and device for self-healing and power restoration of a distribution network fault, which can solve the problem of low efficiency of self-healing and power restoration of the distribution network in the prior art.

[0005] In order to solve the above technical problems, the present invention provides a method for self-healing and restoring power to a distribution network fault, comprising:

[0006] Construct a mathematical model of the distribution network based on the topological structure information of the distribution network, equipment electrical parameters, load characteristics data, and distributed power access data;

[0007] Acquire fault data corresponding to several types of faults from the historical operation and maintenance data of the distribution network; wherein the fault data includes fault nature, fault location, and fault electrical quantity data;

[0008] Based on each of the fault data, a fault simulation is performed in the distribution network mathematical model to determine a self-healing and power restoration operation rule;

[0009] Collecting the operation data of the distribution network in real time; wherein the operation data includes current current data and current voltage data;

[0010] determining a current fault type of the distribution network according to the operating data;

[0011] Determining, according to the current fault type, device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing power restoration operation rule;

[0012] When the operation data of the distribution network reaches the device action set value, each of the protection devices is isolated in sequence according to the device action sequence, and after the isolation process, the post-isolation operation data of the distribution network is collected;

[0013] determining a fault area and a non-fault area of ​​the distribution network based on the post-isolation operation data;

[0014] The fault area is cut off and the power supply is switched to the non-fault area.

[0015] As a preferred solution, based on each of the fault data, fault simulation is performed in the distribution network mathematical model to determine the self-healing and power restoration operation rules, including:

[0016] For each fault type, determining the fault-affected device and the priority corresponding to each fault-affected device according to the fault location, the topology information of the distribution network, and the distributed power supply access data;

[0017] Determining a trigger data type of the fault-affected device based on the device electrical parameters; wherein the trigger data type includes current and voltage;

[0018] Determining a trigger action constant corresponding to each of the fault-affected devices according to the load characteristic data, the fault electrical quantity data, and the trigger data type;

[0019] Based on the priority and trigger action setting corresponding to each of the fault-affected devices, a self-healing power restoration operation rule for the fault type is determined.

[0020] As a preferred solution, determining the trigger action setting corresponding to each fault-affected device based on the load characteristic data, the fault electrical quantity data, and the trigger data type includes:

[0021] Acquire line data corresponding to the trigger data type from the load characteristic data;

[0022] Obtaining a fault parameter corresponding to the trigger data type from the fault electrical quantity data;

[0023] Based on the line data and the fault parameters, a trigger action setting corresponding to the fault-affected device is determined.

[0024] As a preferred solution, when the trigger data type is current, determining the trigger action constant corresponding to each fault-affected device based on the load characteristic data, the fault electrical quantity data, and the trigger data type includes:

[0025] Obtaining the maximum load current of the line and the maximum short-circuit current at the end of the line from the load characteristic data;

[0026] Obtaining fault current parameters from the fault electrical quantity data;

[0027] When the fault is a permanent fault, determining a current constant corresponding to the equipment affected by the fault according to the maximum load current of the line and the fault current parameter;

[0028] When the fault is of a transient nature, the current constant corresponding to the fault-affected device is determined according to the maximum short-circuit current at the end of the line and the fault current parameter.

[0029] As a preferred solution, when the trigger data type is voltage, determining the trigger action constant corresponding to each fault-affected device based on the load characteristic data, the fault electrical quantity data, and the trigger data type includes:

[0030] Obtaining a line rated voltage from the load characteristic data;

[0031] Obtaining a fault voltage parameter from the fault electrical quantity data;

[0032] A voltage constant corresponding to the fault-affected equipment is determined based on the line rated voltage and the fault voltage parameter.

[0033] As a preferred solution, determining the current fault type of the distribution network according to the operating data includes:

[0034] Converting the current data into a current waveform;

[0035] Converting the current voltage data into a voltage waveform;

[0036] Determining current waveform characteristics based on the current waveform; wherein the current waveform characteristics include current current amplitude, current current phase and current current harmonic content;

[0037] Determining voltage waveform characteristics based on the voltage waveform; wherein the voltage waveform characteristics include current voltage amplitude, current voltage phase, and current voltage harmonic content;

[0038] A current fault type of the power distribution network is determined based on the current waveform characteristics and the voltage waveform characteristics.

[0039] As a preferred solution, the determining of device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing and power restoration operation rules according to the current fault type includes:

[0040] Based on the current fault type, obtaining a plurality of protection devices and a priority of each of the protection devices in the self-healing power restoration operation rule;

[0041] The protection devices are sorted according to their priorities to form a device action sequence.

[0042] As a preferred solution, the removing of the faulty area and the switching of power to the non-faulty area include:

[0043] Determining, in the non-fault area, an area to be transferred adjacent to the fault area;

[0044] After the fault area is removed, load data of the area to be transferred is collected;

[0045] Determining whether the area to be transferred has an overload risk based on the load data;

[0046] When it is determined that the area to be transferred has an overload risk, the connecting switch connected to the fault area is closed.

[0047] As a preferred solution, before isolating each of the protection devices in sequence according to the device action sequence, the method further includes:

[0048] Acquire current distribution network status data; wherein the current distribution network status data includes current authority management data, current protection device status data, current power flow data and current listing data;

[0049] Performing an anti-mistaken lockout detection based on the current distribution network status data; wherein the anti-mistaken lockout detection includes authority anti-mistaken lockout detection, system anti-mistaken lockout detection, flow anti-mistaken lockout detection and listing anti-mistaken lockout detection;

[0050] If it is determined that the anti-mislocking detection is passed, each of the protection devices is isolated in sequence according to the device action sequence.

[0051] Accordingly, the present invention provides a distribution network fault self-healing and power restoration device, comprising: a model building module, a data acquisition module, a fault simulation module, a data acquisition module, a fault property determination module, a protection device determination module, an isolation processing module, an area classification module, and a self-healing and power restoration module;

[0052] The model building module is used to build a distribution network mathematical model based on the topological structure information of the distribution network, equipment electrical parameters, load characteristic data and distributed power supply access data;

[0053] The data acquisition module acquires fault data corresponding to several types of faults from the historical operation and maintenance data of the distribution network; wherein the fault data includes fault nature, fault location and fault electrical quantity data;

[0054] The fault simulation module performs fault simulation in the distribution network mathematical model based on each of the fault data to determine the self-healing and power restoration operation rules;

[0055] The data acquisition module collects the operation data of the distribution network in real time; wherein the operation data includes current current data and current voltage data;

[0056] The fault nature determination module determines a current fault type of the distribution network according to the operation data;

[0057] The protection device determination module determines, according to the current fault type, device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing power restoration operation rule;

[0058] When the operation data of the distribution network reaches the device action set value, the isolation processing module isolates each protection device in sequence according to the device action sequence, and collects the post-isolation operation data of the distribution network after the isolation processing;

[0059] The area classification module determines the fault area and the non-fault area of ​​the distribution network based on the post-isolation operation data;

[0060] The self-healing power restoration module performs power removal processing on the faulty area and switches power to the non-faulty area.

[0061] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0062] The present invention provides a method for self-healing and restoring power after a distribution network fault. The method constructs a mathematical model of the distribution network based on distribution network topology information, equipment electrical parameters, load characteristics, and distributed power supply access data. Fault data corresponding to several fault types is obtained from historical operation and maintenance data of the distribution network. Based on each fault data, fault simulation is performed within the mathematical model to determine self-healing and restoration operation rules. By improving the construction and simulation analysis of the distribution network model, the present invention comprehensively considers various complex fault types and operating condition combinations, thereby generating self-healing and restoration operation rules that can adapt to the complex and changing distribution network environment, thereby improving the accuracy of the self-healing operation rules. The method collects distribution network operating data in real time; determines the current fault type of the distribution network based on the operating data; and determines the device action settings and device action sequence corresponding to several protection devices in the self-healing and restoration operation rules based on the current fault type. When the distribution network operating data reaches the device action setting, each protection device is isolated according to the device action sequence. Based on the basic principle of coordinated differential protection, the present invention isolates protection devices in a hierarchical manner, improving the efficiency of fault area determination and, consequently, self-healing and restoration efficiency. After the isolation process, the system collects post-isolation operational data from the distribution network. Based on this data, it identifies the faulty and non-faulty areas of the distribution network. The faulty areas are then removed, and power is transferred to the non-faulty areas. By transferring power to the non-faulty areas, the load can be quickly and flexibly transferred to other functioning power lines, effectively reducing the scope of the outage, significantly shortening power restoration time, and significantly improving the efficiency of the distribution network's self-healing and power restoration. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the implementation. Obviously, the drawings described below are only some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0064] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for self-healing and restoring power to a distribution network fault provided by the present invention;

[0065] Figure 2 A schematic flow chart of an embodiment of the method for preventing mislocking provided by the present invention;

[0066] Figure 3 A flow chart of another embodiment of the method for self-healing and restoring power to a distribution network fault provided by the present invention;

[0067] Figure 4 This is a structural diagram of an embodiment of the distribution network fault self-healing and power restoration device provided by the present invention. DETAILED DESCRIPTION

[0068] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0069] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0070] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0071] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0072] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0073] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0074] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0075] Example 1

[0076] See also Figure 1 To solve the problem of low efficiency of self-healing and power restoration in distribution networks in the prior art, an embodiment of the present invention provides a method for self-healing and power restoration in distribution networks. The method includes steps 101 to 109, each of which is specifically as follows:

[0077] Step 101: Construct a distribution network mathematical model based on the topological structure information of the distribution network, equipment electrical parameters, load characteristic data, and distributed power access data.

[0078] In an embodiment of the present invention, based on the topological structure information, equipment electrical parameters, load characteristic data and distributed power access data of the actual distribution network, an accurate distribution network mathematical model can be constructed using professional power system modeling technology. Among them, the topological structure information includes the connection relationship of nodes (busbars, transformers, switches, etc.), branch (line, cable) parameters, and network hierarchical structure (high / medium / low voltage). The electrical parameters of the equipment include line impedance (R / X), transformer capacity, transformer ratio, transformer loss, switch action characteristics, capacitor bank capacity, etc. Load characteristics include historical load curves, load types (industrial / residential / commercial), power factor, peak and valley characteristics, and harmonic content. Distributed power access data includes power access location, capacity, power generation characteristics (photovoltaic / wind power intermittency) and control strategy (grid-connected / island mode). After obtaining the relevant data of the actual distribution network, these data are cleaned and standardized. The simulation software DIgSILENT can be used to create a mathematical model of the distribution network using a graphical interface.

[0079] Step 102: Acquire fault data corresponding to several types of faults from the historical operation and maintenance data of the distribution network; wherein the fault data includes fault nature, fault location, and fault electrical quantity data.

[0080] In an embodiment of the present invention, the historical operation and maintenance data of the distribution network includes fault data corresponding to multiple faults. Based on this historical fault data, combined with a mathematical model of the distribution network, self-healing and power restoration rules can be derived that take into account the actual characteristics and operating conditions of distribution networks in different regions. The analyzed historical fault data includes fault type, nature, location, and fault electrical quantity data. Fault types include short circuits, line breaks, equipment failures, external force damage, and operational errors. Fault natures include permanent and transient faults. Permanent faults are those that cannot be corrected automatically and require human intervention. Examples include wire breakage, permanent equipment insulation damage, and cable breakdown. Permanent faults require isolation of the faulted area before power can be restored to non-faulty areas, potentially resulting in prolonged power outages. Transient faults are short-lived (typically within a few seconds) and self-recoverable. Examples include lightning overvoltage causing instantaneous insulator flashover and foreign objects (such as birds or branches) that briefly contact and then fall off a conductor. Transient faults, which can be restored through automatic reclosing, account for approximately 60% to 80% of distribution network faults. Fault electrical quantity data refers to abnormal changes in electrical parameters at various points in the system when a power device or line fails. This data includes current, voltage, power, impedance, and harmonic component data.

[0081] Step 103: Based on the fault data, perform fault simulation in the distribution network mathematical model to determine self-healing and power restoration operation rules.

[0082] In this embodiment of the present invention, the simulation software DIgSILENT can be used to simulate various historical fault scenarios within a distribution network mathematical model, thereby observing the distribution network's response after a fault occurs and extracting key information from the simulation process. Through in-depth analysis of a large amount of simulated fault data, important information such as the key operational steps, equipment operation sequence, and electrical parameter variation patterns during the distribution network power restoration process after a fault occurs are extracted. This allows the system to summarize targeted and actionable power restoration operation rules and instruction features.

[0083] As a preferred solution of this embodiment, based on each of the fault data, a fault simulation is performed in the distribution network mathematical model to determine the self-healing and power restoration operation rules, including:

[0084] For each fault type, determining the fault-affected device and the priority corresponding to each fault-affected device according to the fault location, the topology information of the distribution network, and the distributed power supply access data;

[0085] Determining a trigger data type of the fault-affected device based on the device electrical parameters; wherein the trigger data type includes current and voltage;

[0086] Determining a trigger action constant corresponding to each of the fault-affected devices according to the load characteristic data, the fault electrical quantity data, and the trigger data type;

[0087] Based on the priority and trigger action setting corresponding to each of the fault-affected devices, a self-healing power restoration operation rule for the fault type is determined.

[0088] In an embodiment of the present invention, for each fault type, a fault simulation is performed in a mathematical model of the distribution network based on its corresponding fault data. Based on the fault location and the topological structure information of the distribution network, the topological relationship between each device in the distribution network and the fault location can be determined, for example, the relationship between being connected to the fault location and being separated from the fault location by one device. Combined with the distributed power supply access data, the direction of current flow in the distribution network can be obtained. Combined with the topological relationship between each device in the distribution network and the fault location, multiple fault-affecting devices of the fault type and the impact size between each fault-affecting device and the fault location can be determined. By sorting out the impact size between each fault-affecting device and the fault location, the priority of each fault-affecting device under the fault type can be determined.

[0089] In an embodiment of the present invention, the electrical parameters of each device in the distribution network include device configuration data and fault-time electrical quantity monitoring data. By querying the device configuration data, it is possible to determine whether the device is a current measuring element or a voltage measuring element, and whether the device's external terminals are connected to a current transformer or a voltage transformer. The fault-time electrical quantity monitoring data can reflect the pattern of electrical quantity changes in the device before and after the fault, allowing determination of whether the device experienced significant changes in current or voltage before and after the fault. By analyzing this data, it is possible to determine whether the trigger data type for each fault-affected device is current or voltage.

[0090] In an embodiment of the present invention, the trigger action setting is a protection setting that triggers the operation of disconnecting the fault-affecting equipment from the fault area, including a current setting and a voltage setting. The fault electrical quantity data includes current data, voltage data, power data, impedance data, and harmonic component data, etc., which reflect the operating characteristics and power transmission status of the distribution network components at the time of the fault. The load characteristic data of the distribution network includes the active power and reactive power data of each node collected in the distribution network over a long period of time. By performing a time series analysis on the load characteristic data, a curve of the load change over time can be drawn, and then its periodicity, trend and other characteristics can be analyzed. Taking the load change into consideration when calculating the trigger action setting corresponding to each fault-affecting equipment can avoid the protection malfunction caused by normal load fluctuations.

[0091] In an embodiment of the present invention, after obtaining the priority and trigger action setting of each fault-affecting device corresponding to a specific fault type, detailed, accurate and self-healing and power restoration operation rules that adapt to the actual operation needs of the distribution network can be formulated, thereby providing scientific guidance for the distribution network to achieve rapid and effective self-healing when a fault occurs.

[0092] As a preferred solution of this embodiment, determining the trigger action setting corresponding to each fault-affected device according to the load characteristic data, the fault electrical quantity data, and the trigger data type includes:

[0093] Acquire line data corresponding to the trigger data type from the load characteristic data;

[0094] Obtaining a fault parameter corresponding to the trigger data type from the fault electrical quantity data;

[0095] Based on the line data and the fault parameters, a trigger action setting corresponding to the fault-affected device is determined.

[0096] In this embodiment of the present invention, calculating the trigger action settings corresponding to the fault-affecting device requires line data representing the characteristics of the distribution network lines and fault parameters corresponding to the current fault type. Therefore, when calculating the trigger action settings, it is necessary to first obtain line data from the load characteristic data and fault parameters from the fault electrical quantity data. Then, combining the line data and fault parameters, the trigger action settings corresponding to the fault-affecting device are calculated.

[0097] As a preferred solution of this embodiment, when the trigger data type is current, determining the trigger action setting corresponding to each fault-affected device based on the load characteristic data, the fault electrical quantity data, and the trigger data type includes:

[0098] Obtaining the maximum load current of the line and the maximum short-circuit current at the end of the line from the load characteristic data;

[0099] Obtaining fault current parameters from the fault electrical quantity data;

[0100] When the fault is a permanent fault, determining a current constant corresponding to the equipment affected by the fault according to the maximum load current of the line and the fault current parameter;

[0101] When the fault is of a transient nature, the current constant corresponding to the fault-affected device is determined according to the maximum short-circuit current at the end of the line and the fault current parameter.

[0102] In an embodiment of the present invention, when it is determined that the trigger data type of the fault-affected device is current, different methods are used to determine the trigger action constant value depending on the nature of the fault. To calculate the current constant value, it is necessary to obtain the maximum load current of the line and the maximum short-circuit current at the end of the line, as well as the fault current parameters. The maximum load current of the line refers to the maximum operating current that may occur when the line is in normal operation and continuously operates for a long time. The maximum short-circuit current at the end of the line refers to the maximum instantaneous effective value of the current flowing through the fault point when a fault occurs at the end of the line. If the current fault nature is a permanent fault, the current constant value is determined by combining the maximum load current of the line and the fault current parameters. Specifically, the current constant value is controlled to be greater than the maximum load current of the line to avoid the maximum load current during normal operation of the line and avoid misjudgment; combined with the fault current parameters in historical fault data, the current constant value is determined under the premise that it is greater than the maximum load current of the line. If the current fault nature is a transient fault, the current constant value is determined by combining the maximum short-circuit current at the end of the line and the fault current parameters. Specifically, the current constant is controlled to be greater than the maximum short-circuit current at the end of the line to ensure that the fault will not be triggered to affect the operation of the equipment during normal operation and when an out-of-zone fault occurs. The fault will only be triggered when an in-zone fault occurs, so as to improve the efficiency of self-healing and power restoration. Combined with the fault current parameters in the historical fault data, the current constant is determined on the premise that it is greater than the maximum short-circuit current at the end of the line.

[0103] As a preferred solution of this embodiment, when the trigger data type is voltage, determining the trigger action setting corresponding to each fault-affected device based on the load characteristic data, the fault electrical quantity data, and the trigger data type includes:

[0104] Obtaining a line rated voltage from the load characteristic data;

[0105] Obtaining a fault voltage parameter from the fault electrical quantity data;

[0106] A voltage constant corresponding to the fault-affected equipment is determined based on the line rated voltage and the fault voltage parameter.

[0107] In this embodiment of the present invention, when the trigger data type of the fault-affected device is determined to be voltage, it is necessary to obtain the line rated voltage and fault voltage parameters to calculate the voltage setting value. Specifically, the voltage setting value is controlled to be greater than the minimum operating voltage allowed by the load. The minimum operating voltage can be determined based on the line rated voltage, generally 0.5-0.7 times the line rated voltage. Combined with the fault voltage parameters in historical fault data, the voltage setting value is determined under the premise that it is greater than the minimum operating voltage.

[0108] Step 104: Collecting operating data of the distribution network in real time; wherein the operating data includes current current data and current voltage data.

[0109] In this embodiment of the present invention, real-time operational data of the distribution network is collected. By combining this real-time operational data with the self-healing and power restoration operation rules determined above, a self-healing and power restoration operation corresponding to the current distribution network fault can be matched. Fault analysis of the distribution network requires current and voltage data at the time of the fault. Therefore, when a distribution network fault occurs, real-time operational data collection of the distribution network is necessary.

[0110] Step 105: Determine the current fault type of the distribution network according to the operating data.

[0111] As a preferred solution of this embodiment, determining the current fault type of the distribution network according to the operating data includes:

[0112] Converting the current data into a current waveform;

[0113] Converting the current voltage data into a voltage waveform;

[0114] Determining current waveform characteristics based on the current waveform; wherein the current waveform characteristics include current current amplitude, current current phase and current current harmonic content;

[0115] Determining voltage waveform characteristics based on the voltage waveform; wherein the voltage waveform characteristics include current voltage amplitude, current voltage phase, and current voltage harmonic content;

[0116] A current fault type of the power distribution network is determined based on the current waveform characteristics and the voltage waveform characteristics.

[0117] In an embodiment of the present invention, the current fault type can be determined based on the characteristics of the distribution network operating data. A fault recording device can be used to obtain the current and voltage waveforms at the time of the fault. Based on the amplitude information of the current and voltage waveforms, the nature of the fault can be analyzed. For example, when a phase-to-phase short circuit occurs, the current amplitude near the short circuit point will increase significantly, far exceeding the normal operating current, while the voltage amplitude will drop significantly. The nature of the fault can be analyzed based on the phase information of the current and voltage waveforms. For example, when a single-phase grounding fault occurs, the phase difference between the fault phase current and voltage will be different from that during normal operation. Measuring the current and voltage phases and comparing them with the phases during normal operation can assist in determining the fault type. The nature of the fault can be analyzed based on the harmonic content information of the current and voltage waveforms. When a fault occurs, the waveforms become distorted and the harmonic content increases. Different fault types have different harmonic characteristics. Therefore, by comprehensively analyzing the current and voltage waveform characteristics, the current fault type can be determined.

[0118] Step 106: According to the current fault type, determine the device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing and power restoration operation rules.

[0119] As a preferred solution of this embodiment, according to the current fault type, determining device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing power restoration operation rule includes:

[0120] Based on the current fault type, obtaining a plurality of protection devices and a priority of each of the protection devices in the self-healing power restoration operation rule;

[0121] The protection devices are sorted according to their priorities to form a device action sequence.

[0122] In an embodiment of the present invention, after determining the current fault type of the distribution network, the self-healing and power restoration operation rules can be used to obtain the multiple protection devices corresponding to the current fault type, as well as the priority and device action setting of each protection device for the current fault type. Based on the priority of each protection device, the protection devices can be sorted to form a device action sequence, thereby clarifying the order in which different protection devices will operate during power restoration. The protection devices are triggered in sequence according to the corresponding device action settings, thereby determining the fault area based on the state of the protection devices after activation, and completing the subsequent self-healing and power restoration process.

[0123] Step 107: When the operation data of the distribution network reaches the device action set value, each protection device is isolated in sequence according to the device action sequence, and the post-isolation operation data of the distribution network is collected after the isolation process.

[0124] In an embodiment of the present invention, the specific process of determining the fault area by triggering the action of the protection device is as follows: determine the first protection device according to the device action sequence, obtain the device action setting of the first protection device, determine whether the current distribution network operating data reaches the device action setting, and if so, isolate the first protection device. After the first protection device completes the isolation process, the current distribution network operating data is collected in real time, and whether the fault still exists is determined based on the real-time operating data. If it is determined that the fault no longer exists at this time, the fault area is determined based on the first protection device. If it is determined that the fault still exists at this time, the next protection device is determined according to the device action sequence, and whether the device action setting of the next protection device is reached based on the current operating data. If so, the next protection device is isolated, and the operation is iterated until the fault area is determined. By applying the differential protection principle, the present invention ensures that when a fault occurs, each level of protection can be quickly activated according to the predetermined selective coordination logic. The protection device closest to the fault point is activated first, accurately cutting off the faulty component, avoiding the expansion of the fault range, and improving the accuracy and reliability of self-healing control.

[0125] As a preferred solution of this embodiment, before isolating each of the protection devices in sequence according to the device action sequence, the method further includes:

[0126] Acquire current distribution network status data; wherein the current distribution network status data includes current authority management data, current protection device status data, current power flow data and current listing data;

[0127] Performing an anti-mistaken lockout detection based on the current distribution network status data; wherein the anti-mistaken lockout detection includes authority anti-mistaken lockout detection, system anti-mistaken lockout detection, flow anti-mistaken lockout detection and listing anti-mistaken lockout detection;

[0128] If it is determined that the anti-mislocking detection is passed, each of the protection devices is isolated in sequence according to the device action sequence.

[0129] In this embodiment of the present invention, when it is determined that the protection device can be isolated, it is also necessary to perform anti-incorrect lockout detection to comprehensively ensure the accuracy and safety of the self-healing operation. The anti-incorrect lockout detection includes authority anti-incorrect lockout detection, system anti-incorrect lockout detection, power flow anti-incorrect lockout detection, and signboard anti-incorrect lockout detection.

[0130] As an example of an embodiment of the present invention, see Figure 2, is a flow chart of an embodiment of the anti-error locking method provided by the present invention. The authority anti-error locking detection is specifically as follows: a strict operation authority management system is pre-built, and corresponding authorities are assigned according to the responsibilities and operation requirements of different personnel. The authority management data of the current distribution network is obtained in real time, and whether the authority to isolate the protection equipment is currently possessed is determined based on the authority management data, thereby ensuring that only authorized personnel can operate specific equipment. The system anti-error locking detection is specifically as follows: the equipment status constraint conditions and operation logic verification rules are pre-set, and before isolating the protection equipment, the equipment status data of the current distribution network is obtained in real time, and the conditional verification is performed based on the equipment status data of the current equipment. The operation instructions must comply with the preset logical sequence (such as disconnecting the load side switch first, and then disconnecting the power side switch), etc. Once the conditions are not met, the relevant operations are automatically locked, and a prompt message is given at the same time, thereby effectively avoiding the operator from making an erroneous operation. For example, when the equipment status data indicates that the current equipment is in a maintenance state, the closing operation is prohibited. Flow lockout prevention involves proactively assessing the potential flow changes associated with device isolation, acquiring real-time distribution network flow data, and predicting whether isolating a device could lead to flow anomalies. If a potential flow anomaly is predicted, the system immediately locks the isolation operation and provides early warning information to guide operations personnel in adjusting their operational strategies, ensuring that self-healing operations do not negatively impact the safe and stable operation of the distribution network. Sign-out prevention involves simultaneously placing a physical sign (such as "Do Not Close" or "Occupied") on the device and executing a corresponding virtual sign in the OCS, ensuring real-time synchronization between the two. When device isolation is triggered, the system acquires real-time distribution network sign-out data. When a device is detected as being in the sign-out state, the system automatically blocks all operations related to the device, whether operated on-site or remotely, to prevent misoperation. Sign-out data is shared across the entire OCS system, ensuring that all operators have a clear understanding of the device's current status and operational restrictions, further enhancing operational safety.

[0131] Step 108: Determine the fault area and non-fault area of ​​the power distribution network based on the post-isolation operation data.

[0132] In this embodiment of the present invention, after isolating each protection device sequentially according to the device operation sequence, the system then detects the current operating data of the distribution network and determines whether a fault still exists based on this real-time operating data. If no fault is determined to be present, the fault area can be determined based on the current isolation status of the protection devices. After the fault area is determined, all areas of the distribution network where the fault occurred are designated as non-fault areas.

[0133] Step 109: performing a cut-off process on the faulty area and performing a power transfer process on the non-faulty area.

[0134] In an embodiment of the present invention, after the fault area and non-fault area of ​​the distribution network are determined, the fault area is cut off and the non-fault area is switched to achieve self-healing and power restoration of the distribution network after a fault.

[0135] As a preferred solution of this embodiment, the faulty area is cut off and the non-faulty area is switched to another area, including:

[0136] Determining, in the non-fault area, an area to be transferred adjacent to the fault area;

[0137] After the fault area is removed, load data of the area to be transferred is collected;

[0138] Determining whether the area to be transferred has an overload risk based on the load data;

[0139] When it is determined that the area to be transferred has an overload risk, the connecting switch connected to the fault area is closed.

[0140] In an embodiment of the present invention, when there is a fault area in the distribution network, it is necessary not only to cut off the fault area when performing self-healing and power restoration, but also to conduct a power transfer analysis on the non-fault area adjacent to the fault area. By performing power transfer processing on the non-fault area, the power outage time can be shortened, the power restoration range can be expanded, resource utilization can be optimized, and power supply reliability can be improved. Specifically, the area to be transferred adjacent to the fault area is first determined based on the topological structure information of the distribution network, and the load data of the area to be transferred after the fault area is cut off is collected. Based on the load data of the area to be transferred, it is determined whether the area to be transferred has an overload risk. If it is determined that the area to be transferred has an overload risk, the connecting switch connected to the fault area is closed to transfer part of the load to other lines; if it is determined that the area to be transferred does not have an overload risk, it means that the current fault does not affect the normal operation of the adjacent area, and there is no need to adjust the status of the adjacent switch.

[0141] In an embodiment of the present invention, different fault properties correspond to different self-healing and power restoration operation rules. For example, when a permanent fault is detected (such as a circuit breaker: equipment damage, explosion, equipment failure caused by lightning, etc.), the standard process of "tripping - isolation - transfer" is executed accordingly. When a transient fault is detected (lightning flashover, phase-to-phase short circuit or grounding fault caused by tree barriers, flashover or contamination caused by bird activities, kites, balloons and other foreign objects falling on the distribution network line causing line short circuit fault, etc.), an attempt is made to perform reclosing and then restore power. If power cannot be restored after reclosing, the standard process of "tripping - isolation - transfer" is executed.

[0142] As an example of an embodiment of the present invention, see Figure 3 , is a flow chart of another embodiment of the distribution network fault self-healing and power restoration method provided by the present invention. Different fault properties correspond to different self-healing and power restoration operation rules. The current fault type and current fault property of the distribution network can be determined based on the operating data of the distribution network. Different self-healing and power restoration operation rules can be executed according to the current fault property. When it is judged that the fault property is a permanent fault, tripping isolation is performed, and the power transfer evaluation is started, and the best connecting switch is closed. When it is judged that the fault property is a transient fault, reclosing is started. If the reclosing is successful, the power supply is restored; if the reclosing is unsuccessful, tripping isolation is performed, and the power transfer evaluation is started, and the best connecting switch is closed.

[0143] The implementation of the above embodiment has the following effects:

[0144] The present invention provides a method for self-healing and restoring power after a distribution network fault. The method constructs a mathematical model of the distribution network based on distribution network topology information, equipment electrical parameters, load characteristics, and distributed power supply access data. Fault data corresponding to several fault types is obtained from historical operation and maintenance data of the distribution network. Based on each fault data, fault simulation is performed within the mathematical model to determine self-healing and restoration operation rules. By improving the construction and simulation analysis of the distribution network model, the present invention comprehensively considers various complex fault types and operating condition combinations, thereby generating self-healing and restoration operation rules that can adapt to the complex and changing distribution network environment, thereby improving the accuracy of the self-healing operation rules. The method collects distribution network operating data in real time; determines the current fault type of the distribution network based on the operating data; and determines the device action settings and device action sequence corresponding to several protection devices in the self-healing and restoration operation rules based on the current fault type. When the distribution network operating data reaches the device action setting, each protection device is isolated according to the device action sequence. Based on the basic principle of coordinated differential protection, the present invention isolates protection devices in a hierarchical manner, improving the efficiency of fault area determination and, consequently, self-healing and restoration efficiency. After the isolation process, the system collects post-isolation operational data from the distribution network. Based on this data, it identifies the faulty and non-faulty areas of the distribution network. The faulty areas are then removed, and power is transferred to the non-faulty areas. By transferring power to the non-faulty areas, the load can be quickly and flexibly transferred to other functioning power lines, effectively reducing the scope of the outage, significantly shortening power restoration time, and significantly improving the efficiency of the distribution network's self-healing and power restoration.

[0145] like Figure 4 As shown, based on the above method embodiment, a corresponding device embodiment is provided;

[0146] An embodiment of the present invention provides a distribution network fault self-healing and power restoration device, comprising: a model building module, a data acquisition module, a fault simulation module, a data acquisition module, a fault property determination module, a protection device determination module, an isolation processing module, an area classification module, and a self-healing and power restoration module;

[0147] The model building module is used to build a distribution network mathematical model based on the topological structure information of the distribution network, equipment electrical parameters, load characteristic data and distributed power supply access data;

[0148] The data acquisition module acquires fault data corresponding to several types of faults from the historical operation and maintenance data of the distribution network; wherein the fault data includes fault nature, fault location and fault electrical quantity data;

[0149] The fault simulation module performs fault simulation in the distribution network mathematical model based on each of the fault data to determine the self-healing and power restoration operation rules;

[0150] The data acquisition module collects the operation data of the distribution network in real time; wherein the operation data includes current current data and current voltage data;

[0151] The fault nature determination module determines a current fault type of the distribution network according to the operation data;

[0152] The protection device determination module determines, according to the current fault type, device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing power restoration operation rule;

[0153] When the operation data of the distribution network reaches the device action set value, the isolation processing module isolates each protection device in sequence according to the device action sequence, and collects the post-isolation operation data of the distribution network after the isolation processing;

[0154] The area classification module determines the fault area and the non-fault area of ​​the distribution network based on the post-isolation operation data;

[0155] The self-healing power restoration module performs power removal processing on the faulty area and switches power to the non-faulty area.

[0156] It can be understood that the above-mentioned device embodiment corresponds to the method embodiment of the present invention, which can implement any one of the above-mentioned method embodiments of the present invention to provide a distribution network fault self-healing and power restoration method.

[0157] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Furthermore, in the drawings of the device embodiments provided by the present invention, the connection relationship between modules indicates that they have a communication connection, which may be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement the present invention without inventive effort.

[0158] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for self-recovery and power restoration of a distribution network fault, characterized in that: include: Construct a mathematical model of the distribution network based on the topological structure information of the distribution network, equipment electrical parameters, load characteristics data, and distributed power access data; Acquire fault data corresponding to several types of faults from the historical operation and maintenance data of the distribution network; wherein the fault data includes fault nature, fault location, and fault electrical quantity data; Based on each of the fault data, a fault simulation is performed in the distribution network mathematical model to determine a self-healing and power restoration operation rule; Collecting the operation data of the distribution network in real time; wherein the operation data includes current current data and current voltage data; determining a current fault type of the distribution network according to the operating data; Determining, according to the current fault type, device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing power restoration operation rule; When the operation data of the distribution network reaches the device action set value, each of the protection devices is isolated in sequence according to the device action sequence, and after the isolation process, the post-isolation operation data of the distribution network is collected; determining a fault area and a non-fault area of ​​the distribution network based on the post-isolation operation data; The fault area is cut off and the power supply is switched to the non-fault area.

2. The method for self-recovery of distribution network fault according to claim 1, characterized in that: The method of performing fault simulation in the distribution network mathematical model based on each of the fault data and determining the self-healing and power restoration operation rules includes: For each fault type, determining the fault-affected device and the priority corresponding to each fault-affected device according to the fault location, the topology information of the distribution network, and the distributed power supply access data; Determining a trigger data type of the fault-affected device based on the device electrical parameters; wherein the trigger data type includes current and voltage; Determining a trigger action constant corresponding to each of the fault-affected devices according to the load characteristic data, the fault electrical quantity data, and the trigger data type; Based on the priority and trigger action setting corresponding to each of the fault-affected devices, a self-healing power restoration operation rule for the fault type is determined.

3. The method for self-recovery of distribution network fault according to claim 2, characterized in that: The determining, based on the load characteristic data, the fault electrical quantity data, and the trigger data type, of a trigger action setting corresponding to each fault-affected device includes: Acquire line data corresponding to the trigger data type from the load characteristic data; Obtaining a fault parameter corresponding to the trigger data type from the fault electrical quantity data; Based on the line data and the fault parameters, a trigger action setting corresponding to the fault-affected device is determined.

4. The method for self-recovery and power restoration of a distribution network fault according to claim 3, characterized in that: When the trigger data type is current, determining the trigger action setting corresponding to each fault-affected device according to the load characteristic data, the fault electrical quantity data, and the trigger data type includes: Obtaining the maximum load current of the line and the maximum short-circuit current at the end of the line from the load characteristic data; Obtaining fault current parameters from the fault electrical quantity data; When the fault is a permanent fault, determining a current constant corresponding to the equipment affected by the fault according to the maximum load current of the line and the fault current parameter; When the fault is of a transient nature, the current constant corresponding to the fault-affected device is determined according to the maximum short-circuit current at the end of the line and the fault current parameter.

5. The method for self-recovery and power restoration of distribution network fault according to claim 3, characterized in that: When the trigger data type is voltage, determining the trigger action setting corresponding to each fault-affected device according to the load characteristic data, the fault electrical quantity data, and the trigger data type includes: Obtaining a line rated voltage from the load characteristic data; Obtaining a fault voltage parameter from the fault electrical quantity data; A voltage constant corresponding to the fault-affected equipment is determined based on the line rated voltage and the fault voltage parameter.

6. The method for self-recovery and restoration of power to a distribution network fault according to claim 1, characterized in that: Determining the current fault type of the distribution network according to the operating data includes: Converting the current data into a current waveform; Converting the current voltage data into a voltage waveform; Determining current waveform characteristics based on the current waveform; wherein the current waveform characteristics include current current amplitude, current current phase and current current harmonic content; Determining voltage waveform characteristics based on the voltage waveform; wherein the voltage waveform characteristics include current voltage amplitude, current voltage phase, and current voltage harmonic content; A current fault type of the power distribution network is determined based on the current waveform characteristics and the voltage waveform characteristics.

7. The method for self-recovery and power restoration of a distribution network fault according to claim 2, characterized in that: The determining, according to the current fault type, device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing power restoration operation rule includes: Based on the current fault type, obtaining a plurality of protection devices and a priority of each of the protection devices in the self-healing power restoration operation rule; The protection devices are sorted according to their priorities to form a device action sequence.

8. The method for self-recovery and power restoration of distribution network fault according to claim 1, characterized in that: The performing of a power removal process on the faulty area and a power transfer process on the non-faulty area includes: Determining, in the non-fault area, an area to be transferred adjacent to the fault area; After the fault area is removed, load data of the area to be transferred is collected; Determining whether the area to be transferred has an overload risk based on the load data; When it is determined that the area to be transferred has an overload risk, the connecting switch connected to the fault area is closed.

9. The method for self-recovery and power restoration of distribution network fault according to claim 1, characterized in that: Before isolating each of the protection devices in sequence according to the device action sequence, the method further includes: Acquire current distribution network status data; wherein the current distribution network status data includes current authority management data, current protection device status data, current power flow data and current listing data; Performing an anti-mistaken lockout detection based on the current distribution network status data; wherein the anti-mistaken lockout detection includes authority anti-mistaken lockout detection, system anti-mistaken lockout detection, flow anti-mistaken lockout detection and listing anti-mistaken lockout detection; If it is determined that the anti-mislocking detection is passed, each of the protection devices is isolated in sequence according to the device action sequence.

10. A self-healing device for power distribution network faults, characterized in that: include: Model building module, data acquisition module, fault simulation module, data collection module, fault nature determination module, protection device determination module, isolation processing module, area classification module and self-healing power restoration module; The model building module is used to build a distribution network mathematical model based on the topological structure information of the distribution network, equipment electrical parameters, load characteristic data and distributed power supply access data; The data acquisition module acquires fault data corresponding to several types of faults from the historical operation and maintenance data of the distribution network; wherein the fault data includes fault nature, fault location and fault electrical quantity data; The fault simulation module performs fault simulation in the distribution network mathematical model based on each of the fault data to determine the self-healing and power restoration operation rules; The data acquisition module collects the operation data of the distribution network in real time; wherein the operation data includes current current data and current voltage data; The fault nature determination module determines a current fault type of the distribution network according to the operation data; The protection device determination module determines, according to the current fault type, device action settings and device action sequences corresponding to a plurality of protection devices in the self-healing power restoration operation rule; When the operation data of the distribution network reaches the device action set value, the isolation processing module isolates each protection device in sequence according to the device action sequence, and collects the post-isolation operation data of the distribution network after the isolation processing; The area classification module determines the fault area and the non-fault area of ​​the distribution network based on the post-isolation operation data; The self-healing power restoration module performs power removal processing on the faulty area and switches power to the non-faulty area.

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