A distribution network dispatching control method and system based on power consumption data

Abstract

The present application relates to a distribution network dispatching and control method and system based on power consumption data, comprising: obtaining fault isolation result information, identifying non-fault outage lines and assisting tie switches for non-fault outage lines based on the fault isolation result information; obtaining the circuit transmission loss factor of the substation connected to the tie switch, and screening assisting substations from the substations connected to the tie switch based on the circuit transmission loss factor; obtaining substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, and calculating the assisting capacity factor of the assisting substation based on the substation rated load data, assisting line rated load data, and power consumption data of the assisting substation; and allocating the power consumption of non-fault outage lines based on the assisting capacity factor of the assisting substation and the circuit transmission loss factor. This method can rapidly respond to changes in the distribution network and restore power to non-fault outage lines to the maximum extent possible, at the fastest speed, and with the highest quality.

Description

Technical Field

[0001] The present application relates to the field of distribution network dispatching and control, and in particular to a distribution network dispatching and control method and system based on electricity consumption data. Background Art

[0002] With the advancement of power system automation technology, distribution network dispatching has gradually shifted from a traditional model dominated by manual experience to a rudimentary digital management model. Early dispatching systems relied on data acquisition and supervisory control systems to remotely monitor grid status and perform fault isolation and load distribution based on preset rules. While these systems provided basic fault isolation, they primarily relied on fixed operating modes, manual experience, and equipment parameters to make dispatching decisions, resulting in long dispatch cycles. While these systems were able to maintain basic distribution network operations for a certain period of time, they lacked the ability to fully utilize real-time data and rapidly respond to emergencies.

[0003] Current traditional dispatching methods struggle to adapt to the rapidly changing operational state of the power grid, cannot effectively address the volatility of distribution networks, and struggle to make fast and accurate grid dispatch and control decisions. Furthermore, traditional methods are inefficient when processing large amounts of data and complex network topologies, making them inefficient in meeting the real-time monitoring and tiered protection requirements of modern distribution networks. They also suffer from low resource utilization, rigid coordination mechanisms, and a single fault recovery strategy. Summary of the Invention

[0004] Based on this, it is necessary to provide a distribution network dispatching control method and system based on power consumption data that can quickly respond to changes in the distribution network and restore power to non-fault power outage lines to the maximum extent, fastest speed and highest quality to address the above technical problems.

[0005] In a first aspect, the present application provides a distribution network dispatching and control method based on electricity consumption data, comprising:

[0006] Obtain fault isolation result information, and identify the non-fault outage line and the auxiliary contact switch of the non-fault outage line according to the fault isolation result information;

[0007] Obtaining a circuit transmission loss factor of the substation connected to the tie switch, and selecting an assisting substation from the substation connected to the tie switch based on the circuit transmission loss factor, wherein the circuit transmission loss factor is used to represent the proportion of electric energy loss from the substation to the tie switch;

[0008] obtaining substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, and calculating an assisting capability factor of the assisting substation based on the substation rated load data, assisting line rated load data, and power consumption data of the assisting substation;

[0009] The power load of the non-fault outage line is allocated in combination with the assisting capacity factor of the assisting substation and the circuit transmission loss factor. The power load is used to represent the power consumption data of the non-fault outage line.

[0010] In one embodiment, the power consumption data includes predicted power consumption data, the assistance capability factor includes a predicted assistance capability factor, obtaining substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, and calculating the assistance capability factor of the assisting substation based on the substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, including:

[0011] Obtain forecasted electricity usage data to assist substations;

[0012] Obtain substation rated load data of assisting substations and assisting line rated load data;

[0013] The predicted assistance capability factor of the assisting substation is calculated based on the predicted power consumption data of the assisting substation, the rated load data of the substation and the rated load data of the assisting line.

[0014] In one embodiment, the power load includes a predicted power load, and the power load of the non-fault power outage line is distributed in combination with the assisting capacity factor of the assisting substation and the circuit transmission loss factor, including:

[0015] Calculate the assisting weight of the assisting substation according to the predicted assisting capability factor, circuit transmission loss factor and predicted power load of the assisting substation;

[0016] Allocate the predicted power load of non-fault outage lines according to the assistance weight;

[0017] The expression of assistance weight is:

[0018] ;

[0019] Where, For the The assistance weight of each assisting substation, and Respectively The predicted assistance capability factor of the first assisting substation and the A transmission loss factor of the circuit assisting the substation, To predict the power load, To assist the total number of substations.

[0020] In one embodiment, the distribution network dispatching control method based on power consumption data further includes:

[0021] The predicted comprehensive assistance capability data is calculated based on the predicted assistance capability factor of the assisting substation;

[0022] The predicted power load assistance difference is calculated by subtracting the predicted comprehensive assistance capacity data from the predicted power load;

[0023] If the predicted power load assistance difference is less than a preset power load assistance difference threshold, a power load assistance capability deficiency alarm message is generated.

[0024] In one embodiment, obtaining predicted power consumption data of an assisting substation includes:

[0025] Obtain historical electricity consumption data for assisting substations;

[0026] The historical electricity consumption data of the assisting substation is input into the electricity consumption data prediction model to generate the predicted electricity consumption data of the assisting substation.

[0027] In one embodiment, the predicted electricity usage data includes predicted outgoing line electricity usage data and predicted assisting line branch electricity usage data, the historical electricity usage data includes historical outgoing line electricity usage data and historical assisting line branch electricity usage data, the electricity usage data prediction model includes an outgoing line electricity usage data prediction model and a branch electricity usage data prediction model, and the historical electricity usage data of the assisting substation is input into the electricity usage data prediction model to generate the predicted electricity usage data of the assisting substation, including:

[0028] Input the historical outgoing power consumption data into the outgoing power consumption data prediction model to generate the predicted outgoing power consumption data for assisting the substation;

[0029] Inputting historical power consumption data of the assisting line branch into the branch power consumption data prediction model to generate predicted assisting line branch power consumption data of the assisting substation;

[0030] Among them, the loss functions of the outgoing power consumption data prediction model and the branch power consumption data prediction model include a comprehensive power consumption data correction loss function. The comprehensive power consumption data correction loss function is used to ensure that the outgoing power consumption data prediction result of the outgoing power consumption data prediction model of the assisting substation is consistent with the sum of the branch power consumption data prediction results of the corresponding branch power consumption data prediction model of the assisting substation. The expression of the comprehensive power consumption data correction loss function is:

[0031] ;

[0032] Where, Correct the loss function for comprehensive electricity consumption data, is the total number of time series in the prediction cycle, is the absolute value function, For the The total number of branch switches assisting substations, For the Assisting the substation The first branch power consumption data prediction model corresponding to the branch switch Timing output, For the The first step of the prediction model for outgoing power consumption data corresponding to the outgoing switch of the substation Timing output, and Respectively Assisting the substation The parameters of the branch power consumption data prediction model corresponding to the branch switch and the The parameters of the outgoing power consumption data prediction model corresponding to the outgoing switch of the assisting substation.

[0033] In one embodiment, the expression for predicting the assistance capability factor is:

[0034] ;

[0035] Where, For the The predicted assistance capability factor of each assisting substation, is the minimum function, and Respectively The substation rated load data and the first The auxiliary line rated load data of each auxiliary substation, and Respectively The first one assists the substation to predict the outgoing power consumption data and the The forecast of assisting substations and the power consumption data of line branches are provided.

[0036] In one embodiment, obtaining fault isolation result information includes:

[0037] Obtaining single-cycle power grid data of the sectionalizer, and calculating a first power grid anomaly coefficient of the sectionalizer based on the single-cycle power grid data; if the first power grid anomaly coefficient is greater than a preset first switch power grid anomaly threshold of the sectionalizer, controlling the sectionalizer to open, and identifying a tie switch connected to a line between a branch switch corresponding to the sectionalizer and a boundary switch corresponding to the branch switch as a preselected auxiliary tie switch, the preselected auxiliary tie switch being used to preliminarily identify a discrimination range of the auxiliary tie switch;

[0038] Acquiring first multi-cycle power grid data of the branch switch, and calculating a second power grid anomaly coefficient of the branch switch based on the first multi-cycle power grid data; if the second power grid anomaly coefficient is greater than a preset second switch power grid anomaly threshold of the branch switch, controlling the branch switch to open, and identifying a tie switch connected to a line between the opened branch switch and a boundary switch corresponding to the opened branch switch as a preselected auxiliary tie switch, the preselected auxiliary tie switch being used to preliminarily determine a range of the auxiliary tie switches;

[0039] Obtaining second multi-cycle power grid data and a safety device load factor of the outgoing switch, and calculating a third power grid anomaly coefficient of the outgoing switch based on the second multi-cycle power grid data; if the third power grid anomaly coefficient is greater than a preset third switch power grid anomaly threshold of the outgoing switch or the safety device load factor exceeds a preset safety device load threshold of the outgoing switch, controlling the outgoing switch to open, wherein the sampling period of the second multi-cycle power grid data is greater than the sampling period of the first multi-cycle power grid data;

[0040] The open switches are controlled to reclose in sequence, and the fault isolation result information is obtained based on the switch that is finally locked and closed. The switches include section switches, branch switches and outgoing line switches.

[0041] In one embodiment, identifying a non-fault outage line and an auxiliary tie switch of the non-fault outage line according to the fault isolation result information includes:

[0042] Identify a target power supply station based on the fault isolation result information, where the target power supply station is the power supply station to which the fault line corresponding to the fault isolation result information belongs;

[0043] The switch farthest from the target power supply station in the fault line corresponding to the fault isolation result information is set as the obstacle downstream switch;

[0044] Identify the line between the obstacle downstream switch and the boundary switch corresponding to the obstacle downstream switch as a non-fault power outage line;

[0045] The preselected auxiliary contact switches connected to the non-fault power outage line among the preselected auxiliary contact switches are identified as auxiliary contact switches of the non-fault power outage line.

[0046] In a second aspect, the present application also provides a distribution network dispatching and control system based on electricity consumption data, comprising:

[0047] A fault isolation result acquisition module is used to obtain fault isolation result information and identify non-fault power outage lines and auxiliary contact switches of non-fault power outage lines according to the fault isolation result information;

[0048] An assisting substation screening module is used to obtain a circuit transmission loss factor of the substation connected to the tie switch, and screen out assisting substations from the substations connected to the tie switch based on the circuit transmission loss factor, wherein the circuit transmission loss factor is used to represent the proportion of electric energy loss from the substation to the tie switch;

[0049] an assisting capability factor generating module, for obtaining substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, and calculating the assisting capability factor of the assisting substation based on the substation rated load data, assisting line rated load data, and power consumption data of the assisting substation;

[0050] The power load distribution module is used to distribute the power load of the non-fault power outage line in combination with the assisting capacity factor of the assisting substation and the circuit transmission loss factor. The power load is used to represent the power consumption data of the non-fault power outage line.

[0051] The above-mentioned distribution network dispatching and control method and system based on electricity consumption data can achieve rapid response and positioning after the fault occurs by real-time collection and analysis of fault isolation result information, and quickly identifying non-fault power outage lines and their corresponding auxiliary connecting switches. Compared with the traditional manual section-by-section troubleshooting or reliance on a small number of fault indicators for troubleshooting, it can greatly shorten the fault investigation time before power outage restoration, significantly improve the power supply restoration efficiency of non-fault power outage line areas, and improve the power supply reliability of the distribution network; by integrating the substation rated load data, line carrying capacity data and real-time power consumption data of the assisting substation, an assisting capacity factor evaluation system containing multiple core indicators is constructed, which can quantitatively evaluate the power supply potential and carrying risk of the assisting substation, thereby effectively reducing the overload risk of the assisting substation and the assisting line, and ensuring the stability and safety of the distribution network operation.

[0052] In an illustrative manner, the above-mentioned distribution network dispatching and control method and system based on electricity consumption data can realize the coordinated work between substations in the distribution network. When a fault occurs, it can quickly allocate electric energy resources, restore power supply to non-fault areas, and enhance the power supply elasticity and reliability of the distribution network, thereby providing users with a more stable and reliable power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following is a brief introduction to the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0054] Figure 1A schematic diagram of an application environment for a distribution network dispatching and control method based on power consumption data provided by one embodiment of the present application;

[0055] Figure 2 A schematic diagram of the structural composition of an implementation scenario of a distribution network dispatching control method based on power consumption data provided in one embodiment of the present application;

[0056] Figure 3 A flow chart of a distribution network dispatching control method based on power consumption data provided in one embodiment of the present application;

[0057] Figure 4 A schematic diagram of a specific case of an implementation scenario of a distribution network dispatching control method based on power consumption data provided in one embodiment of the present application;

[0058] Figure 5 A flowchart of a method for obtaining predicted power load provided in one embodiment of the present application;

[0059] Figure 6 A flowchart of another distribution network dispatching control method based on power consumption data provided in one embodiment of the present application;

[0060] Figure 7 A schematic structural diagram of a distribution network dispatching and control system based on electricity consumption data is provided for one embodiment of the present application. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0062] The distribution network dispatching control method based on power consumption data provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the data acquisition terminal 102 and the data response terminal 103 can communicate with the computing platform 101 through the network. The database 104 can store the data that the computing platform 101 needs to process. The database 104 can be integrated on the computing platform 101, or it can be placed on the cloud or other network servers. The data acquisition terminal 102 can obtain the power consumption data of the distribution network, and the computing platform 101 can generate the distribution network dispatching control instructions through the power consumption data of the distribution network obtained by the data acquisition terminal 102. The computing platform 101 can send the generated distribution network dispatching control instructions to the data response terminal 103, and can control the data response terminal 103 to perform distribution network dispatching control operations through the distribution network dispatching control instructions. Among them, the computing platform 101 can be implemented with an independent server or a computing device cluster composed of multiple computing devices.

[0063] The distribution network dispatching control method based on power consumption data provided in the embodiment of the present application can be applied to Figure 2 In the implementation scenario shown, the substation is the starting point of power supply for the distribution network. The substation can convert and adapt high-voltage electricity through internal equipment and then transmit it outward through the outgoing line switch. The substation can be the source of power for the entire power supply line. The outgoing line switch can be installed on the outgoing line side of the substation. It is the first switch device connecting the substation to the external line. It can be used to control the on and off of the entire outgoing line. In the event of a fault, it can quickly cut off the outgoing line power supply and reduce the scope of the power outage. The branch switch can distribute the power of the main line to the branch line. In the event of a branch line fault, the branch switch can cut off the faulty branch to ensure normal power supply to the main line and other branches. The section switch can divide a long line into several sections. When normal, the connection is maintained. When a section fails, the faulty section can be cut off to improve power supply reliability. The faulty line can indicate a short circuit, ground fault, or other fault in that section. The boundary switch can be installed at the entrance of the user transformer or important load and is the boundary point between the user and the distribution network. The user transformer can be the end of the distribution network and can convert the power transmitted by the line again to adapt to the voltage requirements of the user's electrical equipment.

[0064] In an exemplary embodiment of the present application, Figure 3 As shown in the figure, a distribution network dispatching control method based on power consumption data is provided. Figure 1 The computing platform in FIG. 1 is used as an example to illustrate the method, which includes the following steps S301 to S304. In which:

[0065] Step S301: Acquire fault isolation result information, and identify non-fault outage lines and auxiliary tie switches of the non-fault outage lines according to the fault isolation result information.

[0066] Specifically, computing platform 101 can obtain fault isolation result information from a database and, based on the obtained fault isolation result information, identify non-fault-related power outage lines and their auxiliary tie switches. The fault isolation result information may include target substation information for the fault-isolated lines. The auxiliary tie switches can be used to dispatch power to auxiliary substations connected to the non-fault-related power outage lines, thereby rapidly restoring power to the non-fault-related power outage lines.

[0067] Step S302: obtaining a circuit transmission loss factor of the substation connected to the tie switch, and selecting an assisting substation from the substation connected to the tie switch based on the circuit transmission loss factor.

[0068] Specifically, the computing platform 101 can obtain the circuit transmission loss factor of the substation connected to the non-fault power outage line through the connecting switch from the database, and can screen the substation connected to the non-fault power outage line through the connecting switch whose circuit transmission loss factor is less than the preset circuit transmission loss threshold as an assisting substation.

[0069] Alternatively, the circuit transmission loss factor may be used to represent the loss ratio of electric energy from the substation to the tie switch.

[0070] Furthermore, the circuit transmission loss factor can be obtained based on the degree of power loss of the line connected to the substation connected to the non-fault power outage line through the tie switch and the tie switch, and the circuit transmission loss factor can be obtained based on the cumulative multiplication of the segmented circuit transmission loss factors of each section of the line connected to the substation connected to the non-fault power outage line through the tie switch and the tie switch.

[0071] Step S303 , obtaining substation rated load data, assisting line rated load data and power consumption data of the assisting substation, and calculating the assisting capability factor of the assisting substation based on the substation rated load data, assisting line rated load data and power consumption data of the assisting substation.

[0072] Specifically, the computing platform 101 can obtain the preset substation rated load data and assisting line rated load data of the assisting substation from a database. The computing platform 101 can also collect the assisting substation's power consumption data through a data acquisition terminal. The computing platform 101 can calculate the assisting capability factor of the assisting substation based on the assisting substation's substation rated load data, assisting line rated load data, and power consumption data. The assisting substation's power consumption data can include power consumption data for the loads corresponding to each boundary switch of the assisting substation.

[0073] For example, Figure 4As shown, X1T, X2T and X3T in the figure are taken as auxiliary substations for explanation. In the figure, MT is the target substation, X1ST, MST1, MST2, X2ST and X3ST are user transformers, MOS1 is the outgoing line switch of the target substation, X1OS1, X2OS1 and X3OS1 are the outgoing line switches of the assisting substation, MSS1, MSS2, MSS3 and MSS4 are the section switches in the branch of the target substation where the fault line is located, MBRS1 is the branch switch in the branch of the target substation where the fault line is located, MBRS2 is the branch switch of the target substation, MBS1 is the boundary switch in the branch of the target substation where the fault line is located, MBS2 is the boundary switch of the target substation, X1SS1, X1SS2, X2SS1, X2SS2, X2SS3, X3SS1 and X3SS2 are the section switches of the assisting substation, X1BS1, X2BS1 and X3BS1 are the boundary switches of the assisting substation, and MX1TS1, MX2TS1 and X2X3TS1 are tie switches. Among them, MX1TS1 and MX2TS1 are auxiliary contact switches, and the non-fault power outage line is the line between the section switch MSS2 and the boundary switch MBS1.

[0074] Furthermore, auxiliary substation X1T can supply power to non-fault-related power outage lines via a line passing through outgoing switch X1OS1, section switch X1SS1, and auxiliary tie switch MX1TS1. Auxiliary substation X2T can supply power to non-fault-related power outage lines via a line passing through outgoing switch X2OS1, section switch X2SS1, and auxiliary tie switch MX2TS1. Auxiliary substation X3T can supply power to non-fault-related power outage lines via a line passing through outgoing switch X3OS1, section switch X3SS1, tie switch X2X3TS1, section switch X2SS1, and auxiliary tie switch MX2TS1.

[0075] Step S304 : Allocate the power load of the non-fault power outage line in combination with the assisting capability factor of the assisting substation and the circuit transmission loss factor.

[0076] Specifically, the computing platform 101 may allocate the power load of the non-fault power outage line in combination with the calculated assisting capability factor of the assisting substation and a preset circuit transmission loss factor.

[0077] Optionally, the power load may be used to represent the power consumption data of non-fault outage lines.

[0078] In the above-mentioned distribution network dispatching and control method based on electricity consumption data, through the dynamic identification technology based on fault isolation results, combined with the quantitative analysis of circuit transmission loss factors, it is possible to accurately locate non-fault power outage lines and screen out the optimal assisting substation path; through real-time analysis of the grid topology and fault isolation status, combined with the transmission loss factor, it is possible to dynamically exclude high-loss paths, thereby realizing the shortest path optimization of the fault recovery strategy, improving the rationality of the recovery path selection, and reducing the power loss of the recovery path; through the multi-dimensional resource evaluation model, it is possible to dynamically calculate the assisting capacity factor of the assisting substation, so that high-potential assisting substations and assisting lines can be matched preferentially, avoiding overload of the assisting substation or assisting line, and improving the resource utilization of the distribution network. Through the load distribution algorithm with dual-factor fusion, it is possible to improve the response capability of the distribution network in the face of sudden working conditions and the adaptability in the face of complex operating scenarios.

[0079] Specifically, in the above-mentioned distribution network dispatching and control method based on power consumption data, by obtaining fault isolation result information and identifying non-fault outage lines and auxiliary tie switches, it is possible to accurately locate and isolate the fault area of ​​the distribution network, thereby maximizing the maintenance of normal power supply in the non-fault area, reducing the scope of the power outage, and improving power supply reliability. By selecting auxiliary substations from the substations connected to the tie switch based on the circuit transmission loss factor, it is possible to optimize the power transmission path and reduce power loss, thereby saving energy, reducing the operating costs of the distribution network, and improving the efficiency of power transmission. By calculating the assisting capacity factor of the assisting substation, it is possible to comprehensively evaluate the power supply capacity and load margin of the assisting substation, thereby making dispatching decisions more scientific and reasonable, avoiding overload of the assisting substation, optimizing the load distribution of the power grid, ensuring the safe and stable operation of the power grid, and further extending the service life of the power grid equipment. By combining the assisting capacity factor of the assisting substation and the circuit transmission loss factor to allocate the power load of the non-fault outage lines, it is possible to achieve reasonable allocation and efficient utilization of power, ensure the power supply capacity of the substation, further improve the overall operating efficiency and power supply quality of the power grid, and enhance the adaptability of the power supply network to different operating conditions.

[0080] In an optional embodiment of the present application, the power consumption data may include predicted power consumption data, and the assistance capability factor may include a predicted assistance capability factor. Figure 3 and Figure 5 Step S303, obtaining the substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, and calculating the assisting capability factor of the assisting substation based on the substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, may include:

[0081] Step S501: Obtain predicted power consumption data of the assisting substation.

[0082] Step S502: Acquire substation rated load data of the assisting substation and assisting line rated load data.

[0083] Step S503 : calculating the predicted assistance capability factor of the assisting substation according to the predicted power consumption data of the assisting substation, the substation rated load data and the assisting line rated load data.

[0084] Optionally, the predicted power consumption data of the assisting substation may include predicted outgoing line power consumption data and predicted assisting line branch power consumption data. In this case, the expression of the predictive assistance capability factor of the assisting substation may be:

[0085] ;

[0086] Where, For the The predicted assistance capability factor of each assisting substation, is the minimum function, and Respectively The substation rated load data and the first The auxiliary line rated load data of each auxiliary substation, and Respectively The first one assists the substation to predict the outgoing power consumption data and the The forecast of assisting substations and the power consumption data of line branches are provided.

[0087] In the above-mentioned distribution network dispatching and control method based on electricity consumption data, by obtaining the forecast assistance capability factor based on the predicted electricity consumption data, the power supply capacity of the assisting substation in the future period can be estimated in advance, and the power load distribution of the non-fault power outage lines can be planned in advance based on the forecast information, so that the power supply resources can be reasonably arranged in advance and the planning of the power grid dispatching can be enhanced; by making dispatching decisions based on the forecast assistance capability factor, the efficient and optimized configuration of the distribution network resources can be achieved, so that the power load of the non-fault power outage lines can be more reasonably distributed, further improving the overall operation efficiency and power supply quality of the power grid, and enhancing the flexibility and adaptability of the distribution network.

[0088] In an optional embodiment of the present application, the power load may include a predicted power load, see Figure 3 and Figure 5 Step S303, allocating the power load of the non-fault power outage line in combination with the assisting capability factor of the assisting substation and the circuit transmission loss factor, may include:

[0089] Step S504 : calculating the assisting weight of the assisting substation according to the predicted assisting capability factor, the circuit transmission loss factor, and the predicted power load of the assisting substation.

[0090] Step S505 : Allocate the predicted power load of the non-fault power outage lines according to the assistance weights.

[0091] Specifically, assist weight The expression can be:

[0092] ;

[0093] Where, For the The assistance weight of each assisting substation, and Respectively The predicted assistance capability factor of the first assisting substation and the A transmission loss factor of the circuit assisting the substation, is the predicted power load of the non-fault outage line, To assist the total number of substations.

[0094] Optional, A circuit transmission loss factor assisting the substation The expression can be:

[0095] ;

[0096] Where, For the The total number of segment circuits in the auxiliary lines of the auxiliary substations, For the The segmented circuit transmission loss factor of the segmented circuit in the auxiliary line of the auxiliary substation.

[0097] Optional, give The predicted power load of non-fault outage lines that assist substation distribution Load capacity The expression can be:

[0098] In the above-mentioned distribution network dispatching and control method based on electricity consumption data, by combining the predicted assistance capability factor and the circuit transmission loss factor to calculate the assistance weight of the assisting substation, it is possible to accurately distribute the predicted power load of the non-fault power outage lines, thereby optimizing the future load distribution strategy of the power grid and improving the power supply quality and reliability of the power grid; by combining the predicted assistance capability factor, circuit transmission loss factor and assistance weight of the predicted power load of each assisting substation, it is possible to ensure that the calculation results of the assistance weight are accurate and reasonable, thereby improving the intelligence level of distribution network dispatching and further enhancing the robustness and efficiency of power grid dispatching.

[0099] In an optional embodiment of the present application, the distribution network dispatching control method based on power consumption data may further include:

[0100] Specifically, the computing platform may calculate the predicted comprehensive assistance capability data based on the predicted assistance capability factor of the assisting substation.

[0101] Specifically, the calculation platform may calculate the predicted power load assistance difference by subtracting the predicted comprehensive assistance capability data from the predicted power load.

[0102] Specifically, if the predicted power load assistance difference is less than a preset power load assistance difference threshold, the computing platform may generate a power load assistance capability deficiency alarm message.

[0103] Optionally, in response to the generation of an alarm message regarding the lack of power load assistance capability, the computing platform may lower the screening criteria for selecting assisting substations from substations connected to the tie switch based on a circuit transmission loss factor, increase the number of assisting substations, and redistribute the power load.

[0104] Illustratively, in response to the generation of the power load assistance capability deficiency alarm information, power restriction measures may be initiated for the power load during a period corresponding to a predicted power load assistance difference being less than a preset power load assistance difference threshold.

[0105] In an optional embodiment of the present application, obtaining the predicted power consumption data of the assisting substation may include:

[0106] Specifically, the computing platform can obtain historical power consumption data of the assisting substation from the database.

[0107] Specifically, the computing platform may input the historical electricity consumption data of the assisting substation into the electricity consumption data prediction model carried on the computing platform to generate the predicted electricity consumption data of the assisting substation.

[0108] Optionally, the electricity consumption data prediction model may include, but is not limited to, a circular economy neural network model (RNN), a long short-term memory network model (LSTM), and a transformer model (Transformer).

[0109] In an optional embodiment of the present application, the predicted electricity usage data may include predicted outgoing line electricity usage data and predicted assisting line branch electricity usage data, the historical electricity usage data may include historical outgoing line electricity usage data and historical assisting line branch electricity usage data, the electricity usage data prediction model may include an outgoing line electricity usage data prediction model and a branch electricity usage data prediction model, and inputting the historical electricity usage data of the assisting substation into the electricity usage data prediction model to generate the predicted electricity usage data of the assisting substation may include:

[0110] Specifically, the computing platform can input historical outgoing power consumption data into an outgoing power consumption data prediction model installed on the computing platform to generate predicted outgoing power consumption data to assist the substation. The computing platform may include an outgoing switch computing device, and the outgoing power consumption data prediction model may be, but is not limited to, installed on the outgoing switch computing device.

[0111] Specifically, the computing platform can input historical power consumption data for assisting line branches into a branch power consumption data prediction model installed on the computing platform to generate predicted power consumption data for assisting substations. The computing platform may include a branch switch computing device, and the branch power consumption data prediction model may be, but is not limited to, installed on the branch switch computing device.

[0112] Among them, the loss function of the outgoing power consumption data prediction model and the branch power consumption data prediction model can include a comprehensive power consumption data correction loss function. The comprehensive power consumption data correction loss function can be used to ensure that the outgoing power consumption data prediction result of the outgoing power consumption data prediction model of the outgoing switch of the assisting substation is consistent with the sum of the branch power consumption data prediction results of each branch power consumption data prediction model of each branch switch corresponding to the outgoing switch of the assisting substation. The expression of the comprehensive power consumption data correction loss function can be:

[0113] ;

[0114] Where, Correct the loss function for comprehensive electricity consumption data, is the total number of time series in the prediction cycle, is the absolute value function, For the The total number of branch switches assisting substations, For the Assisting the substation The first branch power consumption data prediction model corresponding to the branch switch Timing output, For the The first step of the prediction model for outgoing power consumption data corresponding to the outgoing switch of the substation Timing output, and Respectively Assisting the substation The parameters of the branch power consumption data prediction model corresponding to the branch switch and the The parameters of the outgoing power consumption data prediction model corresponding to the outgoing switch of the assisting substation.

[0115] Indicatively, due to , when assisting the outgoing power consumption data prediction model of the outgoing power consumption data of the substation outgoing switch The branch power consumption data prediction results of each branch power consumption data prediction model of each branch switch corresponding to the outgoing line switch of the assisting substation The smaller the error between the summed values ​​of The closer this term is to 1, the more accurate the loss function of comprehensive electricity consumption data correction is. The closer the value of is to 0, the loss function can be corrected by comprehensive electricity consumption data. Through the back propagation of the outgoing power consumption data prediction model and the parameters of the branch power consumption data prediction model are adjusted synchronously to achieve joint optimization under the physical constraint that the total outgoing power consumption is equal to the sum of the branch power consumption.

[0116] In the above-mentioned distribution network dispatching and control method based on electricity consumption data, by generating predicted electricity consumption data in the electricity consumption data prediction model, it is possible to accurately estimate future electricity demand, provide forward-looking electricity consumption data support for distribution network dispatching, so as to accurately predict future electricity demand and improve the distribution network's ability to cope with future load changes; by subdividing the predicted electricity consumption data into predicted outgoing line electricity consumption data and predicted auxiliary line branch electricity consumption data, and using the corresponding outgoing line electricity consumption data prediction model and branch electricity consumption data prediction model for generation, it is possible to achieve refined prediction of electricity consumption data at different levels, thereby further enhancing the flexibility and reliability of distribution network operation and ensuring the stability of power supply at all levels; by introducing the comprehensive electricity consumption data correction loss function, it is possible to ensure that the sum of the outgoing line electricity consumption data prediction results and the branch electricity consumption data prediction results are consistent, which can ensure the logical rationality and interpretability of the measurement results from the data level, thereby improving the quality of the predicted data, providing a solid data foundation for distribution network dispatching, improving the efficiency of power grid dispatching, effectively reducing the operating risks and maintenance costs of the distribution network, and promoting the development of intelligent power grid dispatching technology.

[0117] In an optional embodiment of the present application, the expression for the predicted assistance capability factor may be:

[0118] ;

[0119] Where, For the The predicted assistance capability factor of each assisting substation, is the minimum function, and Respectively The substation rated load data and the first The auxiliary line rated load data of each auxiliary substation, and Respectively The first one assists the substation to predict the outgoing power consumption data and the The forecast of assisting substations and the power consumption data of line branches are provided.

[0120] Optional, at this time, assist weight The expression can be:

[0121] ;

[0122] Right now:

[0123] ;

[0124] Where, Can be used to measure the The ability to assist substations in bearing the power load, Can be used to measure the Assists the overall load strength of the substation; Can be used to measure the The ability of the auxiliary lines of the auxiliary substation to bear the power load, Can be used to measure the The overall load strength of the auxiliary lines of the auxiliary substation.

[0125] Schematically, in predicting the assistance factor In the actual derivation process of the expression of The expression of The first expression in the formula is not highly correlated with the predicted power consumption data of the assisting substation. A circuit transmission loss factor assisting the substation and predicted power load of non-fault outage lines After elimination, we get the prediction assistance ability factor expression.

[0126] For an alternative embodiment of the application, please refer to Figure 3 and Figure 6 Step S301, obtaining fault isolation result information, and identifying the non-fault outage line and the auxiliary tie switch of the non-fault outage line according to the fault isolation result information, may include:

[0127] Step S601: Obtain single-cycle grid data of the sectionalizer, and calculate a first grid anomaly coefficient of the sectionalizer based on the single-cycle grid data. If the first grid anomaly coefficient is greater than a preset first switch grid anomaly threshold of the sectionalizer, control the sectionalizer to open, and identify the tie switch connected to the line between the branch switch corresponding to the sectionalizer and the boundary switch corresponding to the branch switch as a preselected auxiliary tie switch.

[0128] Optionally, the preselected auxiliary contact switch can be used to preliminarily identify the discrimination range of the auxiliary contact switch.

[0129] Step S602: Acquire first multi-cycle grid data of the branch switch, and calculate a second grid abnormality coefficient of the branch switch based on the first multi-cycle grid data. If the second grid abnormality coefficient is greater than a preset second switch grid abnormality threshold of the branch switch, control the branch switch to open.

[0130] Optionally, the sampling period of the first multi-cycle power grid data may be, but is not limited to, four cycles, five cycles, and six cycles.

[0131] Step S603: obtain the second multi-cycle grid data and safety equipment load coefficient of the outgoing switch, and calculate the third grid abnormality coefficient of the outgoing switch based on the second multi-cycle grid data. If the third grid abnormality coefficient is greater than the preset third switch grid abnormality threshold of the outgoing switch or the safety equipment load coefficient exceeds the preset safety equipment load threshold of the outgoing switch, control the outgoing switch to open.

[0132] Optionally, the sampling period of the second multi-cycle power grid data is greater than the sampling period of the first multi-cycle power grid data.

[0133] Optionally, the sampling period of the second multi-cycle power grid data may be, but is not limited to, eight cycles, ten cycles, and twelve cycles.

[0134] Step S604: Control the open switches to reclose in sequence, and obtain fault isolation result information based on the switch that is finally locked and closed.

[0135] Optionally, the switch may include a section switch, a branch switch and an outgoing line switch.

[0136] In the above-mentioned distribution network dispatching and control method based on electricity consumption data, the single-cycle grid data anomaly detection of the section switch can realize the preliminary positioning and rapid response of the fault; the comprehensive judgment of the multi-cycle grid data of the branch switch and the outgoing line switch can realize the accurate isolation and risk avoidance of the fault; the closed-loop coordination of opening and reclosing can enhance the reliability of fault isolation; the preliminary screening of the auxiliary contact switch can provide a preliminary judgment range for the subsequent determination of the auxiliary contact switch, which is helpful to plan the power supply restoration path in advance, thereby improving the efficiency of rapid power supply restoration in the non-fault power outage line area.

[0137] In an optional embodiment of the present application, please refer to Figure 3 and Figure 6 Step S301, obtaining fault isolation result information, and identifying the non-fault outage line and the auxiliary tie switch of the non-fault outage line according to the fault isolation result information, may include:

[0138] Step S605, identifying the target power supply station based on the fault isolation result information.

[0139] Optionally, the target power supply station may be the power supply station to which the fault line corresponding to the fault isolation result information belongs.

[0140] Step S606: Set the switch farthest from the target power supply station in the fault line corresponding to the fault isolation result information as the obstacle downstream switch.

[0141] Step S607: Identify the line between the faulty downstream switch and the boundary switch corresponding to the faulty downstream switch as a non-fault power outage line.

[0142] Step S608: identifying the pre-selected auxiliary tie switches connected to the non-fault power outage line among the pre-selected auxiliary tie switches as auxiliary tie switches of the non-fault power outage line.

[0143] In the above-mentioned distribution network dispatching and control method based on electricity consumption data, the fault recovery efficiency and distribution network resource utilization can be improved by accurately identifying non-fault power outage lines and assisting in the dynamic matching of tie switches.

[0144] In an exemplary embodiment of the present application, Figure 6 As shown, a distribution network dispatching control method based on power consumption data is provided, which may include:

[0145] Step S601: Obtain single-cycle grid data of the sectionalizer, and calculate a first grid anomaly coefficient of the sectionalizer based on the single-cycle grid data. If the first grid anomaly coefficient is greater than a preset first switch grid anomaly threshold of the sectionalizer, control the sectionalizer to open, and identify the tie switch connected to the line between the branch switch corresponding to the sectionalizer and the boundary switch corresponding to the branch switch as a preselected auxiliary tie switch.

[0146] Step S602: Acquire first multi-cycle grid data of the branch switch, and calculate a second grid abnormality coefficient of the branch switch based on the first multi-cycle grid data. If the second grid abnormality coefficient is greater than a preset second switch grid abnormality threshold of the branch switch, control the branch switch to open.

[0147] Step S603: obtain the second multi-cycle grid data and safety equipment load coefficient of the outgoing switch, and calculate the third grid abnormality coefficient of the outgoing switch based on the second multi-cycle grid data. If the third grid abnormality coefficient is greater than the preset third switch grid abnormality threshold of the outgoing switch or the safety equipment load coefficient exceeds the preset safety equipment load threshold of the outgoing switch, control the outgoing switch to open.

[0148] Step S604: Control the open switches to reclose in sequence, and obtain fault isolation result information based on the switch that is finally locked and closed.

[0149] Step S605: Identify the target power supply station based on the fault isolation result information.

[0150] Step S606: Set the switch farthest from the target power supply station in the fault line corresponding to the fault isolation result information as the obstacle downstream switch.

[0151] Step S607: Identify the line between the faulty downstream switch and the boundary switch corresponding to the faulty downstream switch as a non-fault power outage line.

[0152] Step S608: identifying the pre-selected auxiliary tie switches connected to the non-fault power outage line among the pre-selected auxiliary tie switches as auxiliary tie switches of the non-fault power outage line.

[0153] Step S609: obtaining the circuit transmission loss factor of the substation connected to the tie switch, and selecting the assisting substation from the substation connected to the tie switch based on the circuit transmission loss factor.

[0154] Step S610: obtaining substation rated load data, assisting line rated load data and power consumption data of the assisting substation, and calculating the assisting capability factor of the assisting substation based on the substation rated load data, assisting line rated load data and power consumption data of the assisting substation.

[0155] Step S611 : Allocate the power load of the non-fault power outage line in combination with the assisting capability factor of the assisting substation and the circuit transmission loss factor.

[0156] In the above-mentioned distribution network dispatching and control method based on electricity consumption data, by sequentially controlling the opening operations of the section switch, branch switch and outgoing line switch, the fault area in the distribution network can be quickly and accurately isolated, and the fault area can be quickly isolated, which can reduce the impact of the fault on the overall operation of the distribution network, narrow the scope of power outage, and improve the reliability and stability of power supply; by identifying the target power supply station based on the fault isolation result information, and further identifying the non-fault power outage line and its auxiliary connecting switch, the non-fault power outage line and its auxiliary connecting switch can be accurately located, which can provide a clear target for load transfer and rapid power restoration, thereby optimizing the distribution network dispatching decision, shortening the power restoration time of the non-fault power outage line, and improving the power supply service quality, grid operation and management efficiency and distribution network intelligence level.

[0157] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0158] Based on the same inventive concept, an embodiment of the present application further provides a power consumption data-based distribution network dispatching and control system for implementing the above-mentioned power consumption data-based distribution network dispatching and control method. The implementation solution provided by this system is similar to the implementation solution described in the above-mentioned method. Therefore, the specific limitations of one or more power consumption data-based distribution network dispatching and control system embodiments provided below can be found in the above-mentioned limitations of the power consumption data-based distribution network dispatching and control method, and will not be repeated here.

[0159] In an exemplary embodiment, Figure 7 As shown, a distribution network dispatching and control system 700 based on power consumption data is provided, which may include:

[0160] The fault isolation result acquisition module 701 can be used to acquire fault isolation result information and identify the non-fault outage line and the auxiliary tie switch of the non-fault outage line according to the fault isolation result information.

[0161] The assisting substation screening module 702 can be used to obtain the circuit transmission loss factor of the substation connected to the tie switch and screen out assisting substations from the substations connected to the tie switch based on the circuit transmission loss factor. The circuit transmission loss factor is used to represent the proportion of power loss from the substation to the tie switch.

[0162] The assistance capability factor generation module 703 can be used to obtain the substation rated load data, the assisting line rated load data and the power consumption data of the assisting substation, and calculate the assistance capability factor of the assisting substation based on the substation rated load data, the assisting line rated load data and the power consumption data of the assisting substation.

[0163] The power load distribution module 704 can be used to distribute the power load of the non-fault power outage line in combination with the assisting capability factor of the assisting substation and the circuit transmission loss factor. The power load is used to represent the power consumption data of the non-fault power outage line.

[0164] In an optional embodiment of the present application, the assisting capability factor generation module 703 may also be used to:

[0165] Obtain forecasted electricity usage data to assist substations.

[0166] Obtain substation rated load data of the assisting substation and assisting line rated load data.

[0167] The predicted assistance capability factor of the assisting substation is calculated based on the predicted power consumption data of the assisting substation, the rated load data of the substation and the rated load data of the assisting line.

[0168] In an optional embodiment of the present application, the power load distribution module 704 may also be used to:

[0169] The assisting weight of the assisting substation is calculated according to the predicted assisting capability factor, circuit transmission loss factor and predicted power load of the assisting substation.

[0170] The predicted power load of non-fault outage lines is distributed according to the assistance weight.

[0171] In an optional embodiment of the present application, the power distribution network dispatching and control system 700 based on power consumption data may also be used to:

[0172] The predicted comprehensive assistance capability data is calculated based on the predicted assistance capability factor of the assisting substation.

[0173] The predicted power load assistance difference is calculated by subtracting the predicted comprehensive assistance capability data from the predicted power load.

[0174] If the predicted power load assistance difference is less than a preset power load assistance difference threshold, a power load assistance capability deficiency alarm message is generated.

[0175] In an optional embodiment of the present application, the assisting capability factor generation module 703 may also be used to:

[0176] Obtain historical electricity usage data for assisting substations.

[0177] The historical electricity consumption data of the assisting substation is input into the electricity consumption data prediction model to generate the predicted electricity consumption data of the assisting substation.

[0178] In an optional embodiment of the present application, the assisting capability factor generation module 703 may also be used to:

[0179] The predicted outgoing power consumption data is input into the outgoing power consumption data prediction model to generate the predicted outgoing power consumption data for assisting the substation.

[0180] The historical power consumption data of the assisting line branch is input into the branch power consumption data prediction model to generate the predicted assisting line branch power consumption data of the assisting substation.

[0181] In an optional embodiment of the present application, the fault isolation result acquisition module 701 may also be used to:

[0182] The single-cycle grid data of the sectionalizer is obtained, and the first grid anomaly coefficient of the sectionalizer is calculated based on the single-cycle grid data. If the first grid anomaly coefficient is greater than the preset first switch grid anomaly threshold of the sectionalizer, the sectionalizer is controlled to open, and the connecting switch connected to the line between the branch switch corresponding to the sectionalizer and the boundary switch corresponding to the branch switch is identified as a pre-selected auxiliary connecting switch. The pre-selected auxiliary connecting switch is used to preliminarily identify the judgment range of the auxiliary connecting switch.

[0183] The first multi-cycle grid data of the branch switch is obtained, and the second grid abnormality coefficient of the branch switch is calculated based on the first multi-cycle grid data. If the second grid abnormality coefficient is greater than the preset second switch grid abnormality threshold of the branch switch, the branch switch is controlled to open.

[0184] Obtain the second multi-cycle grid data and safety equipment load coefficient of the outgoing switch, and calculate the third grid abnormality coefficient of the outgoing switch based on the second multi-cycle grid data. If the third grid abnormality coefficient is greater than the preset third switch grid abnormality threshold of the outgoing switch or the safety equipment load coefficient exceeds the preset safety equipment load threshold of the outgoing switch, control the outgoing switch to open.

[0185] The open switches are controlled to reclose in sequence, and the fault isolation result information is obtained based on the switch that is finally locked and closed. The switches include section switches, branch switches and outgoing line switches.

[0186] In an optional embodiment of the present application, the fault isolation result acquisition module 701 may also be used to:

[0187] A target power supply station is identified based on the fault isolation result information, where the target power supply station is the power supply station to which the fault line corresponding to the fault isolation result information belongs.

[0188] The switch farthest from the target power supply station in the fault line corresponding to the fault isolation result information is set as the obstacle downstream switch.

[0189] The line between the obstacle downstream switch and the boundary switch corresponding to the obstacle downstream switch is identified as a non-fault power outage line.

[0190] The preselected auxiliary contact switches connected to the non-fault power outage line among the preselected auxiliary contact switches are identified as auxiliary contact switches of the non-fault power outage line.

[0191] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the distribution network dispatching control method based on electricity consumption data as described above are implemented.

[0192] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0193] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. The device embodiments described above are merely illustrative, wherein the components described as separate parts may or may not be physically separated, and the parts displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the disclosed solution. A person of ordinary skill in the art can understand and implement it without expending creative work.

[0194] The above-described embodiments merely represent several implementation methods of the embodiments of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the concept of the embodiments of the present application, and these modifications and improvements fall within the scope of protection of the embodiments of the present application.

Claims

1. A distribution network dispatching and control method based on power consumption data, characterized in that: The method comprises: Acquiring fault isolation result information, and identifying a non-fault outage line and an auxiliary tie switch of the non-fault outage line according to the fault isolation result information; obtaining a circuit transmission loss factor of the substation connected to the tie switch, and selecting an assisting substation from the substation connected to the tie switch based on the circuit transmission loss factor, wherein the circuit transmission loss factor is used to represent a loss ratio of electric energy from the substation to the tie switch; Obtaining substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, and calculating an assisting capability factor of the assisting substation based on the substation rated load data, the assisting line rated load data, and the power consumption data of the assisting substation; Allocating the power load of the non-fault power outage line in combination with the assisting capability factor of the assisting substation and the circuit transmission loss factor, wherein the power load is used to represent the power consumption data of the non-fault power outage line; The power consumption data includes predicted power consumption data, the assisting capability factor includes a predicted assisting capability factor, and the obtaining of substation rated load data, assisting line rated load data, and power consumption data of the assisting substation, and calculating the assisting capability factor of the assisting substation based on the substation rated load data, the assisting line rated load data, and the power consumption data of the assisting substation includes: Acquiring the predicted power consumption data of the assisting substation, wherein the predicted power consumption data includes predicted outgoing line power consumption data and predicted assisting line branch power consumption data; Acquiring the substation rated load data and the assisting line rated load data of the assisting substation; Calculating the predicted assistance capability factor of the assisting substation based on the predicted power consumption data of the assisting substation, the substation rated load data, and the assisting line rated load data; The expression of the prediction assistance capability factor is: ； Where, For the the predicted assistance capability factor of each of the assisting substations, is the minimum function, and Respectively The substation rated load data of the assisting substation and the The auxiliary line rated load data of each auxiliary substation, and Respectively The predicted outgoing power consumption data of the assisting substation and the The predicted assisting line branch power consumption data of each of the assisting substations.

2. The method according to claim 1, characterized in that The power load includes a predicted power load, and the allocating the power load of the non-fault power outage line in combination with the assisting capability factor of the assisting substation and the circuit transmission loss factor includes: calculating an assistance weight of the assisting substation according to the predicted assistance capability factor of the assisting substation, the circuit transmission loss factor, and the predicted power load; Allocate the predicted power load of the non-fault power outage line according to the assistance weight; The expression of the assistance weight is: ； Where, For the the assistance weight of each of the assisting substations, and Respectively The predicted assistance capability factor of the assisting substation and the the circuit transmission loss factor of the assisting substation, is the predicted electricity load, is the total number of the assisting substations.

3. The method according to claim 2, characterized in that The method further comprises: Calculating predicted comprehensive assistance capability data based on the predicted assistance capability factor of the assisting substation; Subtracting the predicted comprehensive assistance capability data from the predicted power load to calculate a predicted power load assistance difference; If the predicted power load assistance difference is less than a preset power load assistance difference threshold, an power load assistance capability deficiency alarm message is generated.

4. The method according to any one of claims 1 to 3, characterized in that The obtaining of the predicted power consumption data of the assisting substation includes: Obtaining historical electricity consumption data of the assisting substation; The historical power consumption data of the assisting substation is input into a power consumption data prediction model to generate the predicted power consumption data of the assisting substation.

5. The method according to claim 4, characterized in that The historical power consumption data includes historical power consumption data of outgoing lines and historical power consumption data of assisting line branches, the power consumption data prediction model includes an outgoing line power consumption data prediction model and a branch power consumption data prediction model, and inputting the historical power consumption data of the assisting substation into the power consumption data prediction model to generate predicted power consumption data of the assisting substation includes: Inputting the outgoing line historical power consumption data into the outgoing line power consumption data prediction model to generate the predicted outgoing line power consumption data of the assisting substation; Inputting the historical power consumption data of the assisting line branch into the branch power consumption data prediction model to generate the predicted assisting line branch power consumption data of the assisting substation; The loss functions of the outgoing power consumption data prediction model and the branch power consumption data prediction model include a comprehensive power consumption data correction loss function, which is used to ensure that the outgoing power consumption data prediction result of the outgoing power consumption data prediction model of the assisting substation is consistent with the sum of the branch power consumption data prediction results of each branch power consumption data prediction model corresponding to the assisting substation. The expression of the comprehensive power consumption data correction loss function is: ； Where, Correct the loss function for the comprehensive electricity consumption data, is the total number of time series in the prediction cycle, is the absolute value function, For the The total number of branch switches in the auxiliary substation, For the The first of the said assisting substations The first branch power consumption data prediction model corresponding to the branch switch Timing output, For the The first of the outgoing power consumption data prediction models corresponding to the outgoing switch of the assisting substation Timing output, and Respectively The first of the said assisting substations The parameters of the branch power consumption data prediction model corresponding to the branch switch and the Parameters of the outgoing line power consumption data prediction model corresponding to the outgoing line switch of the assisting substation.

6. The method according to claim 1, characterized in that The obtaining of fault isolation result information includes: Acquiring single-cycle grid data of a sectionalizing switch, and calculating a first grid abnormality coefficient of the sectionalizing switch based on the single-cycle grid data; if the first grid abnormality coefficient is greater than a preset first switch grid abnormality threshold of the sectionalizing switch, controlling the sectionalizing switch to open, and identifying a tie switch connected to a line between a branch switch corresponding to the sectionalizing switch and a boundary switch corresponding to the branch switch as a preselected auxiliary tie switch, the preselected auxiliary tie switch being used to preliminarily identify a discrimination range of the auxiliary tie switch; Acquiring first multi-cycle grid data of the branch switch, and calculating a second grid abnormality coefficient of the branch switch based on the first multi-cycle grid data, and controlling the branch switch to open if the second grid abnormality coefficient is greater than a preset second switch grid abnormality threshold of the branch switch; obtaining second multi-cycle power grid data and a safety device load factor of the outgoing switch, and calculating a third power grid abnormality coefficient of the outgoing switch based on the second multi-cycle power grid data; if the third power grid abnormality coefficient is greater than a preset third switch power grid abnormality threshold of the outgoing switch or the safety device load factor exceeds a preset safety device load threshold of the outgoing switch, controlling the outgoing switch to open, wherein a sampling period of the second multi-cycle power grid data is greater than the sampling period of the first multi-cycle power grid data; The open switches are controlled to reclose in sequence, and the fault isolation result information is obtained according to the switch that is finally locked and closed, wherein the switches include the section switch, the branch switch and the outgoing line switch.

7. The method according to claim 6, characterized in that The identifying, according to the fault isolation result information, a non-fault power outage line and an auxiliary tie switch of the non-fault power outage line includes: Identify a target power supply station based on the fault isolation result information, where the target power supply station is the power supply station to which the fault line corresponding to the fault isolation result information belongs; Setting the switch farthest from the target power supply station in the fault line corresponding to the fault isolation result information as a barrier downstream switch; Identify the line between the obstacle downstream switch and the boundary switch corresponding to the obstacle downstream switch as the non-fault power outage line; The preselected auxiliary tie switch connected to the non-fault power outage line among the preselected auxiliary tie switches is identified as the auxiliary tie switch of the non-fault power outage line.

8. A distribution network dispatching and control system based on electricity consumption data, characterized in that: The system includes various functional modules required for implementing the method according to any one of claims 1 to 7.

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