Power restoration method and device for power distribution network, and electronic equipment

Abstract

The invention discloses a power restoration method and device for a power distribution network and electronic equipment. The method belongs to the field of power systems, and comprises the steps that fault information and historical power parameters of a fault section in a power distribution network are acquired in response to a fault of the power distribution network, the fault section is used for representing the position of the fault in the power distribution network, and the historical power parameters are used for representing power parameters used by the fault section in a historical time period; constructing a power restoration path of the power distribution network based on the fault information; power restoration time of the power distribution network is determined based on the fault information and the power restoration path, and target power supply parameters of the power distribution network are determined based on the historical power parameters, the power restoration time is used for representing the time required by the power distribution network from fault occurrence to successful power restoration, and the target power supply parameters are used for representing power parameters required to be provided when the power distribution network successfully restores power; and based on the power restoration parameters, power restoration is carried out on the power distribution network according to the power restoration path. According to the invention, the technical problem of low power restoration efficiency of the power distribution network in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and in particular to a method and device for restoring power to a distribution network, and electronic equipment. Background Art

[0002] In the power system, the distribution network is the key link between power plants and users, and its operational reliability directly affects the continuity and stability of power supply. However, the normal operation of the distribution network is often threatened by various operational risks, including but not limited to natural disasters (such as typhoons, floods, earthquakes), human factors (such as illegal construction, external force damage caused by municipal construction), and equipment aging. In recent years, especially with the increase in extreme weather events and the acceleration of urbanization, the operational risks faced by the distribution network have become increasingly complex, posing a severe challenge to the safe and stable operation of the power system.

[0003] In the above context, when a distribution network fails, rapid and accurate power restoration is crucial to reduce the negative impact of power outages on the social economy. Traditional fault power restoration methods are inefficient, and in emergency situations, especially disaster events, operators face greater risks, including misoperation, misdispatch, and the risk of electric shock. In addition, due to human limitations on information acquisition and processing, the power restoration time is often difficult to accurately predict, which further increases the uncertainty of power restoration operations and affects the efficiency of power restoration. How to build an efficient fault power restoration strategy under a complex and changing operating risk environment is still a major problem facing the field of power system automation.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method and device for power restoration of a distribution network, and electronic equipment, so as to at least solve the technical problem of low power restoration efficiency of a distribution network in the related art.

[0006] According to one aspect of an embodiment of the present invention, a distribution network restoration method is provided, comprising: in response to a fault in the distribution network, obtaining fault information and historical power parameters of a faulty section in the distribution network, wherein the faulty section is used to characterize the location where the fault occurs in the distribution network, and the historical power parameters are used to characterize the power parameters used by the faulty section in a historical time period; constructing a restoration path for the distribution network based on the fault information; determining a restoration time for the distribution network based on the fault information and the restoration path, and determining a target power supply parameter for the distribution network based on the historical power parameters, wherein the restoration time is used to characterize the time required for the distribution network to be successfully restored from the occurrence of a fault, and the target power supply parameter is used to characterize the power parameters required to be provided when the distribution network is successfully restored; and restoring power to the distribution network according to the restoration path based on the restoration parameters.

[0007] Furthermore, a power restoration path of the distribution network is constructed based on the fault information, including: parsing the fault information to determine the fault cause of the distribution network fault and the fault segment identifier of the fault segment; obtaining multiple initial paths that match the fault cause and the fault segment identifier; performing power restoration simulation on the fault segment based on the multiple initial paths according to preset power parameters to obtain multiple power restoration simulation results; and determining a power restoration path from the multiple initial paths based on the multiple power restoration simulation results.

[0008] Furthermore, based on the fault information and the power restoration path, the power restoration time of the distribution network is determined, including: obtaining power grid data matching the power restoration path in the fault information; obtaining a power restoration time calculation model matching the fault cause of the fault; determining a first power parameter of the fault section from historical power parameters, wherein the first power parameter is used to characterize the power parameter corresponding to the fault section when the distribution network operates normally within the historical time period; inputting the power grid data and the first power parameter into the power restoration time calculation model, and determining the power restoration time using the power restoration time calculation model.

[0009] Furthermore, the method also includes: obtaining from a first database a historical power restoration path used by the distribution network when a fault occurs, and a first power restoration time consumed when restoring the distribution network, wherein the first database is used to store a mapping relationship between faults, historical power restoration paths, and the first power restoration time; constructing an initial time calculation model based on the historical power restoration path and the first power restoration time; obtaining a resilience index of the distribution network, and a time impact index corresponding to the cause of the fault, wherein the resilience index is used to characterize the power restoration efficiency when a fault occurs in the distribution network, the time impact index is used to characterize the degree of influence of different time impact factors on the power restoration process of the distribution network in the environment in which the distribution network is located, and the time impact factor is used to characterize the factors that will affect the power restoration process of the distribution network; the initial time calculation model is adjusted based on the resilience index and the time impact index to obtain a power restoration time calculation model.

[0010] Furthermore, obtaining the resilience index of the distribution network includes: obtaining historical load data matching the fault cause from a second database, wherein the second database is used to store the mapping relationship between the fault cause and the historical load data; parsing the historical load data to determine the load loss corresponding to the fault cause, and the fault time period corresponding to the load loss, wherein the load loss is used to characterize the load that the distribution network cannot output when a fault occurs, and the fault time period is used to characterize the time period when the distribution network loses load when a fault occurs; weighted processing is performed on the load losses corresponding to different moments according to the weights corresponding to different moments in the fault time period to obtain weighted load losses at different moments; and integration processing is performed on the weighted load losses at different moments to obtain the resilience index.

[0011] Furthermore, obtaining a time impact index corresponding to the cause of the fault includes: obtaining historical factor values ​​matching the time impact factor and the second power-on time of the distribution network under the time impact factor from a third database, wherein the third database is used to store a mapping relationship between the time impact factor, the factor value, and the second power-on time; obtaining a probability prediction model matching the time impact factor, wherein the probability prediction model is used to characterize a model constructed for the time impact factor for determining the degree of impact of the time impact factor on the second power-on time; and inputting the historical factor value and the second power-on time into the probability prediction model to obtain the time impact index.

[0012] Furthermore, based on the historical power parameters, the target power supply parameters of the distribution network are determined: a second power parameter of the fault section is determined from the historical power parameters, wherein the second power parameter is used to characterize the power parameter of the fault section within the historical time period; based on the second power parameter, a power parameter change curve is constructed; based on the power parameter change curve, the maximum power parameter used by the fault section within the historical time period and the power restoration time is determined; and the target power supply parameter is constructed based on the maximum power parameter.

[0013] Furthermore, the power restoration parameters include: a backup power supply parameter of the distribution network, the backup power supply parameter is used to characterize the power supply parameter used additionally when the target power supply parameter cannot meet the operating requirements of the fault section. The method also includes: obtaining a first power supply parameter of the distribution network, and the current operating parameters of other areas in the distribution network except the fault section, wherein the first power supply parameter is used to characterize the maximum power supply parameter that the distribution network can provide during normal operation; obtaining a first ratio based on the ratio of the first power supply parameter to the target power supply parameter; adjusting the first ratio based on the operating parameter to obtain a second ratio, wherein the second ratio is less than the first ratio; obtaining a third ratio based on the difference between the second ratio and a preset value, and obtaining the backup power supply parameter based on the product of the third ratio and the target power supply parameter.

[0014] According to another aspect of an embodiment of the present invention, a distribution network restoration device is also provided, including: a parameter acquisition module, used to obtain fault information and historical power parameters of a faulty section in the distribution network in response to a fault in the distribution network, wherein the faulty section is used to characterize the location where the fault occurs in the distribution network, and the historical power parameters are used to characterize the power parameters used by the faulty section in a historical time period; a path construction module, used to construct a restoration path of the distribution network based on the fault information; a parameter determination module, used to determine the restoration parameters of the distribution network based on the fault information, the restoration path and the historical power parameters; and a distribution network restoration module, used to restore the distribution network according to the restoration path based on the restoration parameters.

[0015] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0016] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0017] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0018] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0019] According to another aspect of the embodiments of the present invention, a computer program is further provided. When the computer program is executed by a processor, the methods in the embodiments of the present invention are implemented.

[0020] In an embodiment of the present invention, in response to a fault in the distribution network, fault information and historical power parameters of a fault section in the distribution network are obtained; a power restoration path of the distribution network is constructed based on the fault information; a power restoration time of the distribution network is determined based on the fault information and the power restoration path, and a target power supply parameter of the distribution network is determined based on the historical power parameters; based on the power restoration parameters, the distribution network is restored according to the power restoration path. By analyzing the fault information of the above-mentioned fault section, the cause of the fault and the specific location can be determined. Based on the above-mentioned fault cause and specific location, the power restoration path of the distribution network can be quickly constructed, and the distribution network can be further more accurately calculated based on the above-mentioned fault information and the power restoration path. The power restoration time of the power grid. In addition, by analyzing the above historical power parameters, the target power supply parameters that meet the power restoration needs and the overall stability of the distribution network can be set. Through the above steps, combined with the calculated power restoration time and target power supply parameters and other power restoration parameters, the distribution network is restored according to the power restoration path. The fault cause of the fault section can be accurately and quickly restored, and the stability of the distribution network operation after power restoration can be guaranteed, avoiding secondary faults in the distribution network after power restoration, which in turn leads to an extension of the power restoration period, achieving the purpose of reducing the fault response time, thereby achieving the technical effect of improving the power supply rate, and then solving the technical problem of low power restoration efficiency of the distribution network in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0022] Figure 1 is a flow chart of a method for restoring power in a distribution network according to an embodiment of the present invention;

[0023] Figure 2 is a detailed flow chart of a distribution network power restoration method according to an embodiment of the present invention;

[0024] Figure 3 is a structural block diagram of an optional solution library according to an embodiment of the present invention;

[0025] Figure 4 is a schematic diagram of an optional fault briefing generation system according to an embodiment of the present invention;

[0026] Figure 5 is a schematic diagram of optional statistical data according to an embodiment of the present invention;

[0027] Figure 6 is a schematic diagram of a power distribution network restoration device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] According to an embodiment of the present invention, an embodiment of a distribution network restoration method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] Figure 1 is a flow chart of a distribution network restoration method according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0032] Step S102, in response to a fault in the distribution network, obtaining fault information and historical power parameters of a faulty section in the distribution network, wherein the faulty section is used to characterize the location of the fault in the distribution network, and the historical power parameters are used to characterize the power parameters used by the faulty section in a historical time period.

[0033] The above-mentioned fault section may refer to the location where the fault occurs in the distribution network. The above-mentioned fault information may be information used to determine the fault type and fault cause. The above-mentioned historical power parameters may refer to the power parameters used by the fault section in the historical time period, for example, voltage, current, power, load, etc., but not limited thereto.

[0034] In an optional embodiment, considering that when a distribution network fails, it is necessary to accurately locate the cause of the failure in order to quickly and effectively repair the failure, the distribution network restoration system (hereinafter referred to as the restoration system) can obtain the fault information of the fault section in the distribution network to analyze the type and cause of the above-mentioned failure, thereby improving the efficiency of fault repair. Further considering that the distribution network needs to reset the power parameters when restoring power, in order to make the setting of the above-mentioned power parameters more reasonable, the restoration system can obtain the historical power parameters of the fault section in the distribution network, and provide a reference for the power parameter setting when restoring power, thereby improving the operating stability of the distribution network system after restoration of power.

[0035] For example, in order to accurately obtain the above-mentioned fault information and historical power parameters, the distribution network staff can deploy multiple power telemetry devices in the distribution network in advance. When the distribution network operates normally, the above-mentioned multiple power telemetry devices can monitor in real time and feedback the current voltage, current, power, load and other power parameters of the distribution network to the power restoration system. When a fault occurs in the distribution network, according to the changes in the above-mentioned power parameters, the power restoration system can quickly locate the location of the fault, and can further determine the cause of the fault by analyzing the power parameters that have undergone abnormal changes. In addition, since the above-mentioned multiple power telemetry devices feedback power parameters to the power restoration system in real time, the power restoration system can pre-divide the effective time of data storage, which can cover the normal operation data before the distribution network fails. The power restoration system can store the real-time data fed back by the power telemetry devices according to the above-mentioned effective time. After the distribution network fault occurs, the power restoration system can obtain the historical power parameters of the fault section in the distribution network by reading the above-mentioned real-time data, thereby providing data reference for the power parameter setting during power restoration.

[0036] Step S104: constructing a power restoration path for the distribution network based on the fault information.

[0037] The above-mentioned power restoration path may refer to a path for restoring power supply after a failure occurs in the distribution network.

[0038] In an optional embodiment, considering that the location and cause of the fault point can be quickly determined by analyzing the above fault information, the power restoration system can formulate a power restoration path and plan in a targeted manner to quickly restore power supply to the affected area. Therefore, the power restoration system can first analyze the above fault information to obtain specific fault information such as the location of the fault point, fault type, fault phenomenon, and then the power restoration system can further analyze the above specific fault information to determine the cause of the fault. Subsequently, the power restoration system can formulate a power restoration path based on the fault location and fault cause, so that the above power restoration path can provide accurate data support for the formulation of the power restoration plan, thereby improving the accuracy and effectiveness of the power restoration plan, and then improving the efficiency of power restoration.

[0039] For example, the power restoration system has obtained the above fault information. In order to more accurately construct the above power restoration path, the power restoration system can analyze the above fault information. The analysis results show that the above fault occurred in the middle section of line A in the distribution network, and the fault type is overload. Further analysis of the above fault information shows that the fault cause is that the current carried by the above fault section line exceeds the rated value, causing the equipment to overheat. The evaluation system can formulate a power restoration path based on the above fault cause, working location and other information. The path can effectively isolate the fault point to minimize the impact range of the power outage. At the same time, the path can provide a basis for the formulation of a power restoration plan, so that the power restoration system can efficiently formulate a power restoration plan, thereby quickly restoring power supply to the affected area.

[0040] Step S106, based on the fault information and the power restoration path, determine the power restoration time of the distribution network, and based on the historical power parameters, determine the target power supply parameters of the distribution network, wherein the power restoration time is used to characterize the time required for the distribution network to successfully restore power from the occurrence of a fault, and the target power supply parameters are used to characterize the power parameters that need to be provided when the distribution network successfully restores power.

[0041] The above-mentioned power restoration time may refer to the time required for the power distribution network to be successfully restored from the occurrence of a fault. The above-mentioned target power supply parameter may refer to the power parameter required to be provided when the power distribution network is successfully restored.

[0042] In an optional embodiment, considering that the above fault information contains information such as the cause of the fault and the location of the fault, this information determines what restoration measures the power restoration system needs to take to solve the current fault of the distribution network. In addition, the above restoration path determines the implementation environment of the above restoration measures. Simpler restoration measures and implementation environments will make the distribution network restore power supply in a shorter time, while more complex restoration measures and implementation environments will make the distribution network restore power supply in a longer time. Therefore, in order to more accurately determine the restoration time of the distribution network, the restoration system can quantify the time from the occurrence of the fault to the restoration of power supply of the distribution network based on the above fault information and restoration path, that is, the restoration time of the above distribution network. Further considering that the distribution network needs to reset the power parameters when restoring power, if the power parameters are set unreasonably, it may cause a secondary fault of the distribution network, thereby reducing the operating stability of the distribution network. Since the historical power parameters characterize the power parameters used by the above fault section in the historical time period, that is, the power parameters of the above fault section during normal operation, the restoration system can refer to the above historical power parameters to set the target power supply parameters to ensure that the distribution network can operate stably after restoration.

[0043] For example, the power restoration system has formulated the above-mentioned power restoration path. In order to more accurately determine the above-mentioned power restoration time and target power supply parameters, the staff can import the power restoration measures corresponding to common fault types and the implementation complexity of the measures into the power restoration system in advance, so that the power restoration system can quickly generate power restoration measures corresponding to the current fault type. The power restoration system can generate power restoration measures corresponding to the above-mentioned fault types based on the work categories contained in the above-mentioned fault information. Then, the power restoration system can determine the overall implementation complexity of the power restoration measures based on the above-mentioned power restoration path, and further determine the power restoration time based on the above-mentioned complexity. In addition, the power restoration system can determine the target power supply parameters of the distribution network based on historical power parameters and in combination with the changes in the operating status of the distribution network that may occur after the execution of the above-mentioned power restoration measures, so as to improve the stability of the distribution network operation after power restoration.

[0044] Step S108: based on the power restoration parameters, restore power to the distribution network along the power restoration path.

[0045] The above-mentioned power restoration parameters may be parameters required in the process of restoring power supply of the distribution network. For example, the above-mentioned power restoration parameters may at least include the above-mentioned power restoration time and target power supply parameters, but are not limited thereto.

[0046] In an optional embodiment, considering that the power restoration parameters are formulated based on the historical operating parameters of the distribution network, and the above historical operating parameters characterize the various parameters of the faulty section of the distribution network during normal operation, therefore, restoring the distribution network based on the power restoration parameters helps to maintain the stability of the distribution network, avoids large-scale fluctuations or re-tripping caused by improper power restoration operations, and ensures that the power system can operate stably after power restoration. In addition, the above power restoration path is formulated based on the fault cause and fault range of the faulty section of the distribution network. Therefore, the power restoration system restores the distribution network based on the above power restoration parameters and according to the above power restoration path, which can improve the power restoration efficiency and reduce the power outage time.

[0047] In an embodiment of the present invention, in response to a fault in the distribution network, fault information and historical power parameters of a fault section in the distribution network are obtained; a power restoration path of the distribution network is constructed based on the fault information; a power restoration time of the distribution network is determined based on the fault information and the power restoration path, and a target power supply parameter of the distribution network is determined based on the historical power parameters; based on the power restoration parameters, the distribution network is restored according to the power restoration path. By analyzing the fault information of the above-mentioned fault section, the cause of the fault and the specific location can be determined. Based on the above-mentioned fault cause and specific location, the power restoration path of the distribution network can be quickly constructed, and the distribution network can be further more accurately calculated based on the above-mentioned fault information and the power restoration path. The power restoration time of the power grid. In addition, by analyzing the above historical power parameters, the target power supply parameters that meet the power restoration needs and the overall stability of the distribution network can be set. Through the above steps, combined with the calculated power restoration time and target power supply parameters and other power restoration parameters, the distribution network is restored according to the power restoration path. The fault cause of the fault section can be accurately and quickly restored, and the stability of the distribution network operation after power restoration can be guaranteed, avoiding secondary faults in the distribution network after power restoration, which in turn leads to an extension of the power restoration period, achieving the purpose of reducing the fault response time, thereby achieving the technical effect of improving the power supply rate, and then solving the technical problem of low power restoration efficiency of the distribution network in related technologies.

[0048] Furthermore, a power restoration path of the distribution network is constructed based on the fault information, including: parsing the fault information to determine the fault cause of the distribution network fault and the fault segment identifier of the fault segment; obtaining multiple initial paths that match the fault cause and the fault segment identifier; performing power restoration simulation on the fault segment based on the multiple initial paths according to preset power parameters to obtain multiple power restoration simulation results; and determining a power restoration path from the multiple initial paths based on the multiple power restoration simulation results.

[0049] The above-mentioned fault cause may be an external damage event or natural disaster that causes a failure in the distribution network. For example, the above-mentioned fault cause may include at least one or more of the following: municipal construction, illegal construction, accidents, wind disasters, floods, earthquakes. The above-mentioned fault segment identifier may be an identifier used to distinguish different fault segments. The above-mentioned initial path may refer to a path that may meet the actual power restoration demand and may be determined as a power restoration path. The above-mentioned preset power parameters may be pre-set power parameters for simulating the above-mentioned multiple power restoration paths. The above-mentioned power restoration simulation result may be a power restoration effect based on the power restoration simulation of the fault segment based on the above-mentioned multiple initial power restoration paths. For example, the above-mentioned power restoration simulation result may include at least one or more of the following: power restoration efficiency, stability and safety of the power system after power restoration, etc., but is not limited to this.

[0050] In an optional embodiment, considering that the specific location and cause of the fault can be quickly determined by analyzing the fault information, it is beneficial for the power restoration system to take correct power restoration measures and accurately isolate the fault section to prevent the scope of the fault from expanding, thereby protecting the power supply of the non-fault area. Therefore, the power restoration system can first analyze the above fault information to determine the fault cause of the distribution network fault and the fault section identifier of the fault section, thereby improving the accuracy of the power restoration operation of the power restoration system. Further considering that based on the above fault cause and fault section identifier, multiple initial paths can be formulated. In order to accurately select the initial path with higher power restoration efficiency among the above multiple initial paths as the above power restoration path, the power restoration system can set the above preset power parameters based on the historical power parameters of the above fault section during normal operation. Then, the power system can perform power restoration simulation on the above fault section based on the preset power parameters and the multiple initial paths to obtain multiple power restoration simulation results. At this time, the power restoration system can select the initial power restoration path with better power restoration effect as the power restoration path based on the above multiple power restoration simulation results.

[0051] For example, the power restoration system has obtained the fault information of the fault section of the distribution network. In order to ensure the accuracy of the power restoration operation, the power restoration system can pre-build a power restoration simulation model based on a machine learning algorithm. In order to obtain the fault location and fault cause, the power restoration system can parse the above fault information. The analysis results show that the distribution network line A has a fault, and the fault section is marked as B. The power restoration system can further parse that the cable of section B of line A is damaged due to illegal construction. Then, the power restoration system can formulate an initial path C, a processing path D and an initial path E for section B of line A and the fault cause of illegal construction. At this time, the power restoration system can set the preset power parameters according to the historical power parameters of section B of line A during normal operation. Subsequently, the power restoration system can input the above preset power parameters into the above power restoration simulation model, and simulate the initial path C, processing path D and initial path E respectively based on the power restoration simulation model. The simulation results show that the power restoration efficiency of initial path D is higher than that of initial path C and initial path E. In order to quickly restore the power supply of section B of line A, the power restoration system can determine initial path D as the above power restoration path.

[0052] Furthermore, based on the fault information and the power restoration path, the power restoration time of the distribution network is determined, including: obtaining power grid data matching the power restoration path in the fault information; obtaining a power restoration time calculation model matching the fault cause of the fault; determining a first power parameter of the fault section from historical power parameters, wherein the first power parameter is used to characterize the power parameter corresponding to the fault section when the distribution network operates normally within the historical time period; inputting the power grid data and the first power parameter into the power restoration time calculation model, and determining the power restoration time using the power restoration time calculation model.

[0053] The above-mentioned power grid data may refer to the data generated by the distribution network during operation. For example, the above-mentioned power grid data may include at least one or more of the following: power grid topology, equipment status, load demand, voltage level, current value, etc., but not limited to these. The above-mentioned power restoration time calculation model may be an algorithm model for predicting or calculating the time required from the occurrence of a fault to the complete restoration of power supply. For example, the above-mentioned power restoration time calculation model may be a fault tree analysis, a Monte Carlo simulation model, an intelligent decision-making model, etc., but not limited to these. The above-mentioned first power parameter may be the power parameter corresponding to the fault section when the distribution network operates normally during the historical time period.

[0054] In an optional embodiment, considering that the power grid data matching the power restoration path in the fault information may include information such as power grid topology, equipment status, load demand, voltage level, current value, etc., this information can help the power restoration system evaluate the impact of the fault on the power grid topology and normal operation, thereby providing a theoretical basis for the calculation of the power restoration time. Therefore, the power restoration system can first analyze the above fault information to obtain the power grid data matching the power restoration path in the fault information. Further considering that the impact of different fault causes on the distribution network and the complexity of repair are different, the power restoration time can be calculated more accurately by using a power restoration time calculation model matching the fault cause. Therefore, the power restoration system can pre-build multiple power restoration time calculation models based on multiple different fault causes. When it is necessary to calculate the power restoration time of the distribution network under a certain fault cause, the power restoration system can obtain the power restoration time calculation model matching the fault cause to calculate the power restoration time under the fault cause. In addition, in order to ensure that the distribution network can operate more stably after power restoration, the power restoration system can also obtain the power parameters corresponding to the fault section when the distribution network operates normally in the historical time period, that is, the above-mentioned first power parameters. Finally, the power restoration system can input the above-mentioned power grid data and the first power parameter into the power restoration time calculation model corresponding to the current fault cause, so as to determine the power restoration time using the above-mentioned power restoration time calculation model, thereby improving the accuracy of the power restoration time calculation.

[0055] For example, the above-mentioned fault section can be the middle section of the distribution network line A. In order to accurately calculate the power restoration time, the power restoration system can pre-construct a municipal construction power restoration time calculation model, an illegal construction power restoration time calculation model and an earthquake power restoration time calculation model based on the fault causes of municipal construction, illegal construction and earthquake. Then, the power restoration system can obtain the power grid data matching the power restoration path in the fault information. Through the above-mentioned data, it is clear that the current fault cause is illegal construction. Subsequently, the power restoration system can select the power restoration time calculation model corresponding to the illegal construction from the above-mentioned three power restoration time calculation models, that is, the above-mentioned illegal construction power restoration time calculation model. Then, the power restoration system can parse the above-mentioned power parameters to obtain the power parameters corresponding to the middle section of the distribution network line A when the distribution network is operating normally in the historical time period, that is, the above-mentioned first power parameters, as the basis for calculating the power restoration time. Finally, the power restoration system can input the above-mentioned power grid data and the first power parameters into the illegal construction power restoration time calculation model, and the illegal construction power restoration time calculation model can determine the above-mentioned power restoration time through calculation.

[0056] Furthermore, the method also includes: obtaining from a first database a historical power restoration path used by the distribution network when a fault occurs, and a first power restoration time consumed when restoring the distribution network, wherein the first database is used to store a mapping relationship between faults, historical power restoration paths, and the first power restoration time; constructing an initial time calculation model based on the historical power restoration path and the first power restoration time; obtaining a resilience index of the distribution network, and a time impact index corresponding to the cause of the fault, wherein the resilience index is used to characterize the power restoration efficiency when a fault occurs in the distribution network, the time impact index is used to characterize the degree of influence of different time impact factors on the power restoration process of the distribution network in the environment in which the distribution network is located, and the time impact factor is used to characterize the factors that will affect the power restoration process of the distribution network; the initial time calculation model is adjusted based on the resilience index and the time impact index to obtain a power restoration time calculation model.

[0057] The above-mentioned first database may be a database for storing the mapping relationship between faults, historical power restoration paths and the first power restoration time. The above-mentioned historical power restoration path may refer to the power restoration path that has been used to deal with distribution network faults caused by external failure events. The above-mentioned first power restoration time may refer to the time consumed to restore power to the distribution network using the above-mentioned historical power restoration path. The above-mentioned initial time calculation model may refer to a power restoration time calculation model preliminarily constructed based on the above-mentioned historical power restoration path and the first power restoration time. The above-mentioned resilience index may refer to the power restoration efficiency when a distribution network fault occurs. The above-mentioned time impact index may refer to the degree of influence of different time influencing factors on the power restoration process of the distribution network. For example, the above-mentioned time impact index may be a parameter related to an external failure event or a parameter related to a natural disaster, but is not limited to this. The above-mentioned time influencing factor may refer to a factor that will affect the power restoration process of the distribution network.

[0058] In an optional embodiment, considering that the historical power restoration path includes the resource allocation and scheduling strategies adopted in the past under different fault scenarios, and the time consumed by using the above historical power restoration path, that is, the above first power restoration time, reveals the time overhead of different power restoration operation processes. Therefore, when a similar fault occurs in the distribution network, the power restoration system can obtain the above historical power restoration path and time in the first database, and build an initial time calculation model based on the historical power restoration path and time, so as to preliminarily calculate the power restoration time with the help of historical data. Further considering that the actual power restoration time may be affected by many factors, such as fault type, grid structure, resource availability, etc., and the power restoration efficiency, that is, the above resilience index, and the time impact index reflect the specific impact of these factors on the power restoration time, in order to more accurately calculate the power restoration time, the power restoration system can obtain the resilience index of the distribution network and the time impact index corresponding to the fault cause, and adjust the input parameters of the above initial time calculation model based on the above resilience index and time impact index, so as to build a more accurate power restoration time calculation model.

[0059] For example, in order to improve the calculation accuracy of the power restoration time, the power restoration system can construct the above-mentioned first database based on multiple faults, and the historical power restoration paths and first power restoration times corresponding to the multiple faults in advance. When a fault occurs in the distribution network, the power restoration system can analyze the cause of the fault through the above-mentioned fault information. The cause of the fault can be municipal construction. The power restoration system can further read the historical power restoration path and the first power restoration time corresponding to the municipal construction from the above-mentioned first database based on the above-mentioned fault cause. Then, the power restoration system can construct an initial time calculation model for municipal construction based on the above-mentioned historical power restoration path and the first power restoration time. Subsequently, the power restoration system can obtain the resilience index of the distribution network and the time impact index corresponding to the municipal construction. The above-mentioned resilience index can be the power restoration efficiency of the distribution network, and the above-mentioned time impact index corresponding to the municipal construction can be a personnel scheduling delay index, a pre-construction coordination time index, etc. The power restoration system can adjust the input parameters of the above-mentioned initial time calculation model of the municipal construction based on the above-mentioned power restoration efficiency, personnel scheduling delay index, and pre-construction coordination time index to construct a more accurate municipal construction power restoration time calculation model, thereby improving the calculation accuracy of the municipal construction power restoration time.

[0060] Furthermore, obtaining the resilience index of the distribution network includes: obtaining historical load data matching the fault cause from a second database, wherein the second database is used to store the mapping relationship between the fault cause and the historical load data; parsing the historical load data to determine the load loss corresponding to the fault cause, and the fault time period corresponding to the load loss, wherein the load loss is used to characterize the load that the distribution network cannot output when a fault occurs, and the fault time period is used to characterize the time period when the distribution network loses load when a fault occurs; weighted processing is performed on the load losses corresponding to different moments according to the weights corresponding to different moments in the fault time period to obtain weighted load losses at different moments; and integration processing is performed on the weighted load losses at different moments to obtain the resilience index.

[0061] The second database may be a database for storing a mapping relationship between fault causes and historical load data. The historical load data may be distribution network load data in a time range before the current moment. The load loss may refer to the load that the distribution network cannot output when a fault occurs. The fault time period may refer to the time period when the distribution network loses load when a fault occurs. The weighted load loss may be the load loss obtained by weighting the load loss corresponding to different moments.

[0062] In an optional embodiment, considering that understanding the differences in load loss caused by different types of faults (such as external damage events, natural disasters, etc.) can help the power restoration system to formulate more targeted emergency response and recovery strategies, the power restoration system can first obtain historical load data matching the cause of the fault from the second database, and by analyzing the above historical load data, the power restoration system can determine the load loss corresponding to the above fault cause. Further considering that electricity demand is time-sensitive, the impact of load loss at different times on users and society may be different. Therefore, the power restoration system can also determine the fault time period corresponding to the load loss by analyzing historical load data. In addition, due to the differences in the importance of the load and the sensitivity of the fault time, the power restoration system can perform weighted processing on the load loss corresponding to different times according to the importance of the load or the degree of impact on the user, and obtain weighted load loss at different times to ensure that the most important load is restored first at the critical moment. In order to further reflect the speed and efficiency of power supply restoration of the power grid, the power restoration system can integrate the weighted load loss at different times to calculate the above-mentioned resilience index. The larger the integral value, the longer the power grid recovery time is, that is, the lower the resilience is. Conversely, the smaller the integral value, the shorter the power grid recovery time is, that is, the higher the resilience is.

[0063] For example, in order to accurately obtain the above resilience index to accurately reflect the power restoration efficiency of the distribution network under different types of faults, the power restoration system can construct the above second database based on the mapping relationship between the fault cause and the historical load data in advance. When the distribution network fails, the power restoration system can first analyze that the fault cause of the above fault is an earthquake. At this time, the power restoration system can obtain the historical load data matching the earthquake from the second database, and analyze the historical load data to determine the load that the distribution network cannot output when it fails due to the earthquake, so as to reflect the impact of the fault caused by the earthquake on the power supply service of the distribution network. Subsequently, the power restoration system can perform weighted processing on the corresponding load loss at different times according to the weights corresponding to different times in the fault time period, that is, different weights are assigned according to the importance of the load or the degree of impact on the user, so as to obtain the weighted load loss at different times. Since the power consumption during the day is large, the interruption of the load during this period has a more significant impact on social and economic activities, and the power consumption at night is small, and the interruption of the load during this period has a slighter impact on social and economic activities. Therefore, the weight of the above load loss during the day is higher, and the weight at night is lower, so as to ensure that the daytime power supply is restored first at critical moments. Finally, the power restoration system can integrate the weighted load losses at different times to calculate the above resilience index, thereby reflecting the cumulative impact of load loss over time during the entire period from the distribution network failure due to the earthquake to the full restoration of power supply.

[0064] Furthermore, obtaining a time impact index corresponding to the cause of the fault includes: obtaining historical factor values ​​matching the time impact factor and the second power-on time of the distribution network under the time impact factor from a third database, wherein the third database is used to store a mapping relationship between the time impact factor, the factor value, and the second power-on time; obtaining a probability prediction model matching the time impact factor, wherein the probability prediction model is used to characterize a model constructed for the time impact factor for determining the degree of impact of the time impact factor on the second power-on time; and inputting the historical factor value and the second power-on time into the probability prediction model to obtain the time impact index.

[0065] The third database may be a database for storing the mapping relationship between the time influencing factors, factor values ​​and the second power restoration time. The historical factor value may refer to the degree of influence of the influencing factors on the power restoration process of the distribution network in the power restoration process before the current power restoration process. The second power restoration time may refer to the time taken to restore power to the distribution network under the influence of the historical factor value. The probability prediction model may be a model for determining the degree of influence of the time influencing factors on the second power restoration time.

[0066] In an optional embodiment, considering that the power restoration time of the distribution network is affected by multiple factors, and the same or similar time influencing factors may have similar influence on the power restoration time, in order to improve the power restoration efficiency for the current fault, the power restoration system can predict the influence of the same or similar time influencing factors that may appear in the current power restoration process based on the historical data of the above-mentioned time influencing factors. Therefore, the power restoration system can first obtain the influence of the power restoration process of the distribution network that matches the above-mentioned time influencing factors in history from the above-mentioned third database, that is, the above-mentioned historical factor value. At the same time, the power restoration system can also obtain the time spent on power restoration of the distribution network under the influence of the above-mentioned historical factor value from the above-mentioned third database, that is, the above-mentioned second power restoration time. In order to further quantify the influence of the time influencing factors on the second power restoration time, the power restoration system can pre-construct a probability prediction model that matches the time influencing factors based on the probability prediction theory, and then the power restoration system can input the above-mentioned historical factor value and the second power restoration time into the above-mentioned probability prediction model, and the model can obtain the above-mentioned time influence index through calculation.

[0067] For example, in order to efficiently obtain the time influence index of the above-mentioned time influence factor, the power restoration system can construct the above-mentioned third database in advance based on the mapping relationship between the time influence factor, the factor value and the second power restoration time. When it is necessary to obtain the time influence index of the above-mentioned time influence factor, the power restoration system can obtain the historical factor value matching the time influence factor from the above-mentioned third database, assuming that the time influence factor can be the degree of damage to the distribution network structure caused by illegal construction. At the same time, the power restoration system can also obtain the second power restoration time corresponding to the above-mentioned assumed time influence factor from the above-mentioned third database. Specifically, the above-mentioned second power restoration time can be the time-consuming to repair the structure. Then, the power restoration system can construct a probability prediction model corresponding to the degree of damage to the distribution network structure based on the probability prediction theory, and input the historical factor value corresponding to the degree of damage to the distribution network structure and the above-mentioned second power restoration time into the above-mentioned probability prediction model. Finally, the model can obtain the time influence index corresponding to the degree of damage to the distribution network structure through calculation, thereby providing a calculation basis for the power restoration time of the distribution network failure caused by the above-mentioned illegal construction.

[0068] Furthermore, based on the historical power parameters, the target power supply parameters of the distribution network are determined, including: determining a second power parameter of the fault section from the historical power parameters, wherein the second power parameter is used to characterize the power parameter of the fault section within the historical time period; constructing a power parameter change curve based on the second power parameter; determining the maximum power parameter used by the fault section within the historical time period and the power restoration time based on the power parameter change curve; and constructing the target power supply parameter based on the maximum power parameter.

[0069] The second power parameter may be a power parameter of the fault section in a historical time period. The target power supply parameter may be a power parameter that enables the fault section of the distribution network to operate stably after power is restored.

[0070] In an optional embodiment, taking into account the power parameters of the faulty section in the historical time period during the power restoration process, the power restoration system can be guided to determine the normal load level of the above-mentioned faulty section, so as to avoid reaching an overload state immediately upon power restoration and causing a secondary fault, thereby avoiding the power restoration working cycle from becoming longer. Therefore, in order to improve the power restoration efficiency, the power restoration system can first determine the power parameters of the faulty section in the historical time period from the historical power parameters, that is, the above-mentioned second power parameters. In order to further quantify the power parameter fluctuations of the faulty section in the historical time period, the power restoration system can construct a power parameter change curve of the faulty section based on the above-mentioned second power parameters. Based on the power parameter change curve, the power restoration system can determine the maximum power parameters used by the faulty section in the historical time period and the power restoration time. Since the above-mentioned maximum power parameters can provide a basis for parameter setting in the power restoration process, ensuring that the power parameters will not exceed the safety range when the power supply is restored, the power restoration system can construct the target power supply parameters based on the above-mentioned maximum power parameters.

[0071] For example, the above-mentioned fault section can be section B in distribution network line A. The power restoration system has obtained the historical power parameters of the fault section shown. In order to ensure that the distribution network can operate stably after power restoration, the power restoration system can first determine the power parameters of section B in distribution network line A in the historical time period from the historical power parameters, that is, the above-mentioned second power parameters. Then, in order to construct the power parameter change curve of section B in distribution network line A, the power restoration system can first perform pre-processing operations such as data cleaning and data smoothing on the above-mentioned second power parameters. In addition, the power restoration system can also average or aggregate the pre-processed data at a certain time interval as needed, for example, aggregating second-level data into minute-level data, so as to more intuitively reflect the change trend of the power parameters of section B in distribution network line A. Based on the above-mentioned processed data, the power restoration system can draw a curve of the above-mentioned second power parameter changing with time, that is, the power parameter change curve of section B in distribution network line A. Based on the curve, the power restoration system can further analyze the maximum power parameters used by section B in distribution network line A during the historical time period and the power restoration time. In order to ensure that the power parameters of the distribution network after power restoration do not exceed the boundaries of safe operation, the power restoration system can determine the target power supply parameters of section B in distribution network line A based on the above maximum power parameters, thereby avoiding overload, short circuit and other situations that may cause distribution network failure or damage after power restoration, thereby improving the power restoration efficiency.

[0072] Furthermore, the power restoration parameters include: a backup power supply parameter of the distribution network, the backup power supply parameter is used to characterize the power supply parameter used additionally when the target power supply parameter cannot meet the operating requirements of the fault section. The method also includes: obtaining a first power supply parameter of the distribution network, and the current operating parameters of other areas in the distribution network except the fault section, wherein the first power supply parameter is used to characterize the maximum power supply parameter that the distribution network can provide during normal operation; obtaining a first ratio based on the ratio of the first power supply parameter to the target power supply parameter; adjusting the first ratio based on the operating parameter to obtain a second ratio, wherein the second ratio is less than the first ratio; obtaining a third ratio based on the difference between the second ratio and a preset value, and obtaining the backup power supply parameter based on the product of the third ratio and the target power supply parameter.

[0073] The above-mentioned backup power supply parameter may be an additional power supply parameter used when the target power supply parameter cannot meet the operating requirements of the fault section. The above-mentioned first power supply parameter may be the maximum power supply parameter that the distribution network can provide during normal operation. The above-mentioned first ratio may refer to the ratio of the above-mentioned first power supply parameter to the target power supply parameter. The above-mentioned second ratio may refer to the value after the first ratio is adjusted based on the operating parameter. The above-mentioned third ratio may be the difference between the above-mentioned second ratio and a preset value.

[0074] In an optional embodiment, considering that while restoring power to the above-mentioned faulty section, it is also necessary to ensure the normal operation of other areas in the distribution network except the faulty section, therefore, the power restoration system can obtain the maximum power supply parameters that the distribution network can provide during normal operation, that is, the above-mentioned first power supply parameters. At the same time, the power restoration system can obtain the current operating parameters of other areas in the distribution network except the faulty section. The above-mentioned first power supply parameters and operating parameters can provide a data basis for the reasonable allocation of the power load of the power restoration system, thereby preventing the distribution network from entering an unstable state again due to a sudden increase in load when power is restored. Further considering that the above-mentioned target power supply parameters may be difficult to meet the operating requirements of the faulty section after power is restored, in order to avoid insufficient power supply after power restoration and cause economic losses, the power restoration system can reasonably set the above-mentioned standby power supply parameters to prevent the above-mentioned insufficient power supply phenomenon. Specifically, the power restoration system can first calculate the above-mentioned first ratio based on the ratio of the first power supply parameter to the target power supply parameter. In order to prevent the above-mentioned backup power supply parameters from being too high, thereby affecting the normal operation of other areas in the distribution network except the fault section, the power restoration system can further adjust the first ratio based on the above-mentioned operating parameters, calculate the above-mentioned second ratio, and obtain the above-mentioned third ratio based on the difference between the above-mentioned second ratio and the preset value. Finally, the power restoration system can obtain the backup power supply parameters based on the product of the above-mentioned third ratio and the target power supply parameters.

[0075] For example, the target power supply parameter may be A, and the preset value may be set to 1. In order to enable the above-mentioned backup power supply parameters to provide power reserve for power restoration and ensure stable operation of other areas in the distribution network except the fault section, the power restoration system can first obtain the maximum power supply parameter that the distribution network can provide during normal operation as B, and can obtain the current operating parameters of other areas in the distribution network except the fault section as C. Then, the power restoration system can calculate the above-mentioned first ratio as B / A based on the ratio of the first power supply parameter and the target power supply parameter. In order to more carefully control the increase of load to avoid overloading the entire distribution network, the power restoration system can adjust the first ratio based on the above-mentioned operating parameters to reduce the first ratio, thereby obtaining the above-mentioned second ratio as (BD) / A, wherein D can be the adjustment value of the first ratio determined by the power restoration system according to the above-mentioned operating parameters. The power restoration system can further calculate the above-mentioned third ratio as 1-(BD) / A based on the difference between the above-mentioned second ratio and the preset value, and can calculate the product of the above-mentioned third ratio and the target power supply parameter, thereby obtaining the above-mentioned backup power supply parameter as 1-B+D, which can ensure the normal operation of the entire distribution network while completing the power restoration operation.

[0076] It should be noted that all the values ​​mentioned above, including the preset values, are only for illustrative purposes. The staff can set them according to actual needs and are not limited here.

[0077] For ease of understanding, Figure 2 is a detailed flow chart of a distribution network restoration method according to an embodiment of the present invention, such as Figure 2As shown, the power restoration system can pre-establish a solution library, which can contain better power restoration path solutions for different types of power grid accidents (such as external failure events and natural disasters). In addition, the solution library is designed with a storage module for collecting and storing fault information and fault briefs for subsequent analysis and call. When a fault occurs in the distribution network, the power restoration system can check the node, thereby generating a fault node and isolating the fault segment. Then, the power restoration system can further read the power grid data information of the distribution network, integrate the above information, form a fault brief, and save the fault brief to the storage module of the above solution library for subsequent analysis of the cause of the fault. According to the above generated fault brief, the power restoration system can determine the type of fault (external failure event or natural disaster) and construct a curve model. The curve model takes into account the relationship between the weighted loss of load and time of the distribution network under the fault to improve the accuracy of the power restoration decision. After completing the construction of the above curve model, the power restoration system can read the power load of the users in the fault segment from the distribution network at the time of the fault in the past month to calculate the user's power demand and ensure the smooth progress of the power restoration process. In addition, the power restoration system can also construct backup power supply parameters according to the user's load power demand, and reserve power based on the parameters to prevent power shortages during power restoration, causing economic losses or affecting user power consumption. After completing the above steps, the power restoration system can select a solution. Specifically, the power restoration system can quickly simulate the accident power restoration path according to the above fault type, and select a power restoration solution with higher power restoration efficiency from the above solution library, thereby replacing traditional manual decision-making or experience judgment to improve power restoration efficiency. After completing the selection of the power restoration path solution, the power restoration system can calculate the power restoration time based on the above power restoration path solution and the accurate calculation model of the total time for handling distribution network faults. Then, the power restoration system can perform power restoration operations, and at the same time start or adjust the reserve power according to the user's current power consumption to ensure that the current is stable and avoid safety hazards caused by abnormal values. After the power restoration is completed, the power restoration system can collect data that characterizes the city's power consumption and power grid fluctuation data over a period of time. The power restoration system can upload the data to the above solution library to improve the strategies in the solution library and record the causes of the power outage area to provide data support for subsequent power grid construction. Finally, the power restoration system can sort out the recorded causes of power outages and carry out targeted processing on the faulty section of the power grid to reduce future power outages caused by the same reasons and improve the stability and security of the power grid.

[0078] Figure 3 is a structural block diagram of an optional solution library according to an embodiment of the present invention, such as Figure 3As shown in the figure, the solution library consists of three parts: accident events, power restoration switch execution events, and power flow sections. Among them, accident events represent the types of accidents stored in the solution library, including external damage events (such as municipal construction, illegal construction and accidents) and natural disaster events (such as wind disasters, floods and earthquakes). Each event type has corresponding power restoration strategies and path information. The power restoration switch execution event involves the operation record of the switch during the power restoration process. The operation of the switch is the key operation to achieve power restoration. The power flow section refers to the power flow in the power system at a specific moment. The power flow section information stored in the solution library is related to different accident events and power restoration paths, which helps to analyze the impact of faults on the power system and the system status after the power restoration operation, thereby ensuring the safety and stability of the power restoration process. By associating and storing accident events, power restoration switch execution events and power flow section information, the solution library can provide fast and accurate decision support for the power restoration system, reduce fault recovery time, and improve the safety and efficiency of power system operation.

[0079] Figure 4 is a schematic diagram of an optional fault report generating system according to an embodiment of the present invention, such as Figure 4As shown in the figure, the fault report generation system can include the following modules: fault report generation module, fault handling process time consumption statistics module, fault power calculation module and fault analysis and evaluation module. Among them, the fault report generation module is responsible for collecting and integrating all key information related to fault handling, including the specific time of the fault, the root cause of the fault, the scope of the fault impact (such as the distribution transformers involved, the number of users) and the final handling results. By refining and summarizing this information, a clear fault report is generated to facilitate subsequent analysis and archiving. The fault handling process time consumption statistics module records the time of each key node change from the occurrence of the fault to the complete restoration of power supply, including the tripping of the automatic switch, the isolation of the fault section, the determination of the power restoration path, the power reserve, the start and completion of the power restoration operation, etc. The fault power calculation module records and calculates the operating status of each distribution transformer under the influence of the power outage for each power outage event, including the time of power outage and restoration, the duration of the power outage, and the operating power before the fault. The power loss due to the power outage and the power that can be restored if the power is restored in advance are calculated. This part of the data is crucial for evaluating the economic impact of the fault and optimizing the power dispatching strategy. The fault analysis and evaluation module combines the analysis data, fault release records, planned power outage data and the specific operation data of the dispatcher in the distribution management system to comprehensively evaluate the efficiency and quality of fault handling from three levels: terminal action, distribution master station analysis and remote control execution. Through the joint action of the above modules, it is ensured that the generation of fault briefings is not only a record of the fault handling process, but also an in-depth analysis of the cause of the fault, handling efficiency, economic impact and recovery effect. Through such a comprehensive fault briefing, the power restoration system can promptly identify potential problems in fault handling, take measures to avoid similar faults in the future, and optimize the power restoration strategy to improve the overall operating efficiency and reliability of the distribution network.

[0080] Figure 5 is a schematic diagram of an optional statistical data according to an embodiment of the present invention, such as Figure 5 As shown, the statistical data can include the power consumption data of the blackout area and the power grid fluctuation data of the blackout area. The collection and analysis of the power consumption data of the blackout area helps to more accurately evaluate the impact of the fault on the user load and whether the power reserve is sufficient and reasonable. At the same time, by comparing the power consumption before and after the fault, we can further understand the user's power demand pattern and provide a basis for optimizing the power restoration strategy. The power grid fluctuation data of the blackout area can indicate the state of the power grid in the fault section, including the fluctuation of voltage, current and frequency. By analyzing these data, the power restoration system can identify the weak links of the power grid, especially in the sensitive period after the fault is restored. This will help to carry out targeted strengthening of the distribution network in the future and reduce the risk of the power grid failing again due to fluctuations.

[0081] According to an embodiment of the present invention, an embodiment of a power distribution network restoration device is provided. It should be noted that the device can be used to execute the above power distribution network restoration method. The specific implementation method and application scenario are the same as the above embodiment and will not be repeated here. Figure 6 is a schematic diagram of a power distribution network restoration device according to an embodiment of the present invention. Figure 6 As shown, the device comprises:

[0082] The parameter acquisition module 602 is used to obtain fault information and historical power parameters of the fault section in the distribution network in response to a fault in the distribution network, wherein the fault section is used to characterize the location where the fault occurs in the distribution network, and the historical power parameters are used to characterize the power parameters used by the fault section in a historical time period.

[0083] The path construction module 604 is used to construct a power restoration path of the distribution network based on the fault information.

[0084] The parameter determination module 606 is used to determine the power restoration time of the distribution network based on the fault information and the power restoration path, and to determine the target power supply parameters of the distribution network based on the historical power parameters, wherein the power restoration time is used to characterize the time required for the distribution network to be successfully restored from the occurrence of a fault, and the target power supply parameters are used to characterize the power parameters that need to be provided when the distribution network is successfully restored.

[0085] The distribution network restoration module 608 is used to restore the power to the distribution network according to the restoration path based on the restoration parameters.

[0086] Furthermore, the path construction module is also used to: parse the fault information to determine the cause of the fault in the distribution network and the fault segment identifier of the fault segment; obtain multiple initial paths that match the fault cause and the fault segment identifier; perform power restoration simulation on the fault segment based on the multiple initial paths according to preset power parameters to obtain multiple power restoration simulation results; and determine the power restoration path from the multiple initial paths based on the multiple power restoration simulation results.

[0087] Furthermore, the parameter determination module is also used to: obtain power grid data matching the power restoration path in the fault information; obtain a power restoration time calculation model matching the fault cause of the fault; determine a first power parameter of the fault section from historical power parameters, wherein the first power parameter is used to characterize the power parameter corresponding to the fault section when the distribution network operates normally within a historical time period; input the power grid data and the first power parameter into the power restoration time calculation model, and determine the power restoration time using the power restoration time calculation model.

[0088] Furthermore, the device also includes: a first acquisition module, used to obtain from a first database a historical power-restoration path used by the distribution network when a fault occurs, and a first power-restoration time consumed when restoring the distribution network, wherein the first database is used to store a mapping relationship between faults, historical power-restoration paths and the first power-restoration time; a first construction module, used to construct an initial time calculation model based on the historical power-restoration path and the first power-restoration time; a second acquisition module, used to obtain a resilience index of the distribution network, and a time impact index corresponding to the cause of the fault, wherein the resilience index is used to characterize the power-restoration efficiency when a fault occurs in the distribution network, and the time impact index is used to characterize the degree of influence of different time impact factors on the power-restoration process of the distribution network in the environment in which the distribution network is located, and the time impact factor is used to characterize the factors that will affect the power-restoration process of the distribution network; a third acquisition module, used to adjust the initial time calculation model based on the resilience index and the time impact index to obtain a power-restoration time calculation model.

[0089] Furthermore, the second acquisition module is also used to: obtain historical load data matching the fault cause from the second database, wherein the second database is used to store the mapping relationship between the fault cause and the historical load data; parse the historical load data to determine the load loss corresponding to the fault cause, and the fault time period corresponding to the load loss, wherein the load loss is used to characterize the load that the distribution network cannot output when a fault occurs, and the fault time period is used to characterize the time period when the distribution network loses load when a fault occurs; according to the weights corresponding to different times in the fault time period, weighted processing is performed on the load loss corresponding to different times to obtain weighted load loss at different times; and integration processing is performed on the weighted load loss at different times to obtain a resilience index.

[0090] Furthermore, the second acquisition module is also used to: obtain historical factor values ​​matching the time influencing factors and the second power restoration time of the distribution network under the time influencing factors from the third database, wherein the third database is used to store the mapping relationship between the time influencing factors, the factor values ​​and the second power restoration time; obtain a probability prediction model matching the time influencing factors, wherein the probability prediction model is used to characterize a model constructed for the time influencing factors and used to determine the degree of influence of the time influencing factors on the second power restoration time; input the historical factor values ​​and the second power restoration time into the probability prediction model to obtain the time influence index.

[0091] Furthermore, the parameter determination module is also used to: determine a second power parameter of the fault section from historical power parameters, wherein the second power parameter is used to characterize the power parameter of the fault section within a historical time period; construct a power parameter change curve based on the second power parameter; determine the maximum power parameter used by the fault section within the historical time period and the power restoration time based on the power parameter change curve; and construct the target power supply parameter based on the maximum power parameter.

[0092] Furthermore, the power restoration parameters include: a backup power supply parameter of the distribution network, the backup power supply parameter is used to characterize the power supply parameter used additionally when the target power supply parameter cannot meet the operating requirements of the fault section. The device also includes: a fourth acquisition module, used to obtain a first power supply parameter of the distribution network, and the current operating parameters of other areas in the distribution network except the fault section, wherein the first power supply parameter is used to characterize the maximum power supply parameter that can be provided by the distribution network during normal operation; a first calculation module, used to obtain a first ratio based on the ratio of the first power supply parameter to the target power supply parameter; a second calculation module, used to adjust the first ratio based on the operating parameter to obtain a second ratio, wherein the second ratio is less than the first ratio; a third calculation module, used to obtain a third ratio based on the difference between the second ratio and a preset value, and obtain the backup power supply parameter based on the product of the third ratio and the target power supply parameter.

[0093] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0094] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0095] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0096] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0097] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0098] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0100] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0101] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0102] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of 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, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0103] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for restoring power to a distribution network, characterized in that: include: In response to a fault in the distribution network, acquiring fault information and historical power parameters of a fault section in the distribution network, wherein the fault section is used to characterize a location where the fault occurs in the distribution network, and the historical power parameters are used to characterize power parameters used by the fault section in a historical time period; Constructing a power restoration path of the distribution network based on the fault information; Based on the fault information and the power restoration path, determine the power restoration time of the distribution network, and based on the historical power parameters, determine the target power supply parameters of the distribution network, wherein the power restoration time is used to characterize the time required for the distribution network to successfully restore power from the occurrence of the fault, and the target power supply parameters are used to characterize the power parameters required to be provided when the distribution network successfully restores power; Based on the power restoration parameters, the power distribution network is restored along the power restoration path.

2. The method according to claim 1, characterized in that: Constructing a power restoration path of the distribution network based on the fault information, including: Analyze the fault information to determine the cause of the fault in the distribution network and the fault segment identifier of the fault segment; Acquire multiple initial paths matching the fault cause and the fault segment identifier; According to preset power parameters, based on the multiple initial paths, a power restoration simulation is performed on the fault section to obtain multiple power restoration simulation results; The power restoration path is determined from the plurality of initial paths based on the plurality of power restoration simulation results.

3. The method according to claim 1, characterized in that Determining a power restoration time of the distribution network based on the fault information and the power restoration path includes: Acquire power grid data matching the power restoration path in the fault information; Acquire a power-on time calculation model that matches the fault cause of the fault; Determine a first power parameter of the fault section from the historical power parameters, wherein the first power parameter is used to characterize the power parameter corresponding to the fault section when the distribution network operates normally within the historical time period; The power grid data and the first power parameter are input into the power restoration time calculation model, and the power restoration time is determined using the power restoration time calculation model.

4. The method according to claim 3, characterized in that The method further comprises: Acquire, from a first database, a historical power restoration path used by the distribution network when the fault occurs, and a first power restoration time consumed when restoring the distribution network, wherein the first database is used to store a mapping relationship between the fault, the historical power restoration path, and the first power restoration time; Based on the historical power restoration path and the first power restoration time, construct an initial time calculation model; Obtaining a resilience index of the distribution network and a time impact index corresponding to the fault cause, wherein the resilience index is used to characterize the power restoration efficiency of the distribution network when the fault occurs, and the time impact index is used to characterize the degree of influence of different time impact factors on the power restoration process of the distribution network in the environment in which the distribution network is located, and the time impact factor is used to characterize the factors that will affect the power restoration process of the distribution network; The initial time calculation model is adjusted based on the toughness index and the time impact index to obtain the power restoration time calculation model.

5. The method according to claim 4, characterized in that Obtaining the resilience index of the distribution network, including: Acquire historical load data matching the fault cause from a second database, wherein the second database is used to store a mapping relationship between the fault cause and the historical load data; Parsing the historical load data to determine the load loss corresponding to the fault cause and the fault time period corresponding to the load loss, wherein the load loss is used to characterize the load amount that the distribution network cannot output when the fault occurs, and the fault time period is used to characterize the time period when the distribution network generates the load loss when the fault occurs; According to the weights corresponding to different moments in the fault time period, weighted processing is performed on the load loss corresponding to different moments to obtain weighted load loss at different moments; The weighted load loss at different moments is integrated to obtain the toughness index.

6. The method according to claim 4, characterized in that Obtaining the time impact indicator corresponding to the fault cause includes: Acquire a historical factor value matching the time influencing factor and a second power restoration time of the distribution network under the time influencing factor from a third database, wherein the third database is used to store a mapping relationship between the time influencing factor, the factor value and the second power restoration time; Acquire a probability prediction model that matches the time influencing factor, wherein the probability prediction model is used to characterize a model constructed for the time influencing factor and used to determine the degree of influence of the time influencing factor on the second power restoration time; The historical factor value and the second power restoration time are input into the probability prediction model to obtain the time impact index.

7. The method according to claim 1, characterized in that Determining a target power supply parameter of the distribution network based on the historical power parameter includes: Determine a second power parameter of the fault section from the historical power parameter, wherein the second power parameter is used to characterize the power parameter of the fault section within a historical time period; Based on the second power parameter, construct a power parameter change curve; Based on the power parameter change curve, determine the maximum power parameter used by the fault section during the historical time period and the power restoration time; The target power supply parameter is constructed based on the maximum power parameter.

8. The method according to claim 7, characterized in that The power restoration parameters include: backup power supply parameters of the distribution network, the backup power supply parameters are used to represent additional power supply parameters used when the target power supply parameters cannot meet the operating requirements of the fault section, and the method further includes: Acquire a first power supply parameter of the distribution network and current operating parameters of other areas in the distribution network except the fault section, wherein the first power supply parameter is used to characterize the maximum power supply parameter that can be provided by the distribution network during normal operation; Obtaining a first ratio based on a ratio of the first power supply parameter to the target power supply parameter; Adjusting the first ratio based on the operating parameter to obtain a second ratio, wherein the second ratio is smaller than the first ratio; Based on the difference between the second ratio and a preset value, a third ratio is obtained, and based on the product of the third ratio and the target power supply parameter, the backup power supply parameter is obtained.

9. A power distribution network restoration device, characterized in that: include: A parameter acquisition module, configured to acquire, in response to a fault in the distribution network, fault information and historical power parameters of a fault section in the distribution network, wherein the fault section is used to characterize a location where the fault occurs in the distribution network, and the historical power parameters are used to characterize power parameters used by the fault section in a historical time period; A path construction module, used to construct a power restoration path of the distribution network based on the fault information; a parameter determination module, configured to determine the power restoration time of the distribution network based on the fault information and the power restoration path, and to determine the target power supply parameters of the distribution network based on the historical power parameters, wherein the power restoration time is used to characterize the time required for the distribution network to be successfully powered on from the occurrence of the fault, and the target power supply parameters are used to characterize the power parameters required to be provided when the distribution network is successfully powered on; The distribution network restoration module is used to restore the power to the distribution network according to the restoration path based on the restoration parameters.

10. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 8 when running.

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