An intelligent power distribution control system based on the Internet of Things

Abstract

The present invention discloses an intelligent power distribution control system based on the Internet of Things, which relates to the field of power distribution technology and includes a control center, wherein the control center is communicated and / or electrically connected with a data acquisition module, a data processing module, a data analysis module and a power distribution decision module; the power data of each line node in each power node in the power distribution substation is monitored in real time, and a dynamic model of the power distribution substation is constructed according to the collected power data, and it is judged whether there is an abnormality in the operation of each power node and each line node in the power node. If there is an abnormality, a corresponding load adjustment plan is generated according to the abnormality, and the control center performs temporary power load scheduling according to the generated load adjustment plan, so that when an abnormality occurs in the power distribution substation, a more reasonable and adaptive power scheduling plan can be given to reduce the impact of the abnormality.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution, and in particular to an intelligent power distribution control system based on the Internet of Things. Background Art

[0002] With the introduction of the concept of ubiquitous power Internet of Things and the construction of national smart grids, the process of informationization of power systems has also been rapidly promoted. The gradual enrichment of the development needs of smart distribution networks is testing the efficiency and reliability of smart distribution systems and their communication systems. However, due to the large scale, large number of nodes and wide coverage of the distribution network, the data transmission efficiency of the distribution communication network is low. How to solve these limitations and improve the data transmission efficiency of the distribution communication network, so as to better realize the intelligence of the distribution network, has become a key issue in current research;

[0003] In the prior art, when an abnormality occurs in the distribution network, it is necessary to investigate the location where the abnormality occurs, and then process the abnormal point according to the investigation result. This method will make it impossible to solve the abnormality in the distribution network in time. How to achieve power monitoring of the distribution network while reducing the impact of the abnormality when an abnormality occurs, thereby improving the operation efficiency of the distribution network, is a problem we need to solve. To this end, an intelligent distribution control system based on the Internet of Things is now provided. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent power distribution control system based on the Internet of Things.

[0005] The object of the present invention can be achieved by the following technical solutions: An intelligent power distribution control system based on the Internet of Things, comprising a control center, wherein the control center is communicatively and / or electrically connected to a data acquisition module, a data processing module, a data analysis module, and a power distribution decision module;

[0006] The data acquisition module is composed of several data acquisition units and is used to collect power data of each monitoring node in the distribution station area;

[0007] The data processing module is used to construct a distribution substation area model, and update the distribution substation area model according to the collected power data to obtain a distribution substation area dynamic model;

[0008] The data analysis module is used to analyze the operating status of the dynamic model of the power distribution area, determine whether there is any abnormality in the power distribution status in the power distribution area, and if there is any abnormality, generate a power distribution dispatch instruction;

[0009] The power distribution decision module is used to perform power distribution scheduling on the power distribution station area according to the generated power distribution scheduling module.

[0010] Furthermore, a plurality of power nodes are arranged in the distribution substation area, each power node is used as a monitoring node, and a data acquisition unit is arranged in each monitoring node;

[0011] Several distribution lines are arranged between each power node, and line nodes that are the same in number as the distribution lines are arranged in the monitoring node, and each line node is associated with a distribution line;

[0012] The data acquisition unit collects the power data of the monitoring node and each line node in the monitoring node in real time, and the power data includes current value and voltage value.

[0013] Furthermore, the process of constructing the distribution station area model by the data processing module includes:

[0014] Construct a two-dimensional plane coordinate system, and generate virtual monitoring points corresponding to each monitoring node in the two-dimensional plane coordinate system;

[0015] Setting a virtual line point for the virtual monitoring point, each virtual line point being associated with a line node, and setting a line state for each virtual line point, the line state including a normal state and an abnormal state;

[0016] Setting a load mark for the virtual line point according to the type of the line node associated with the virtual line point in each virtual monitoring point, wherein the load mark includes an input load mark and an output load mark;

[0017] Generate a corresponding virtual line at a corresponding virtual line point according to the distribution line between the monitoring nodes, and set a line type label for the virtual line according to the load mark of the virtual line point connected to the virtual line, wherein the line type label includes an input line label and an output line label;

[0018] Generate a corresponding line point matrix according to two virtual line points connected by the virtual line, the line point matrix including two matrix items, and associate the generated line point matrix with the virtual line;

[0019] A data transmission link is constructed, and the matrix items are communicatively connected with the data acquisition units of the corresponding line nodes through the data transmission link, thereby completing the construction of the distribution station area model.

[0020] Furthermore, the data processing module updates the distribution substation area model according to the collected power data, and the process of obtaining the distribution substation area dynamic model includes:

[0021] Construct a two-dimensional coordinate system of time with respect to current value and voltage value;

[0022] Generate corresponding current change curves and voltage change curves from the power data obtained by each data acquisition unit;

[0023] Mapping the generated current change curve and voltage change curve into a two-dimensional coordinate system to obtain a power parameter change graph;

[0024] Setting a voltage threshold interval and a current threshold interval in the power parameter variation diagram;

[0025] Set the data update cycle T;

[0026] The initial time is recorded as t0, the current time is recorded as t1, and the interval from t0 to t1 is recorded as t;

[0027] Mark the current change curve and voltage change curve between time t0 and time t1;

[0028] When t<T, and the voltage change curve and the current change curve corresponding to the time t1 are within the corresponding voltage threshold interval and current threshold interval, then at t=T, the line state corresponding to the virtual line point is updated to a normal state, and the current change curve and the voltage change curve in the time period from t0 to t1 are intercepted and imported into the matrix item corresponding to the virtual line point, and the corresponding current standard value and voltage standard value are generated;

[0029] By iterating the generated current standard value and voltage standard value in the matrix item, the data iteration of the distribution substation area model is completed, and the corresponding distribution substation area dynamic model is obtained.

[0030] Furthermore, when t<T, and any of the voltage change curve and the current change curve corresponding to time t1 is not within the corresponding voltage threshold interval and current threshold interval, the corresponding change curve is marked as an abnormal curve, and when t=T, the virtual line point corresponding to the abnormal curve is marked as an abnormal line point, the current change curve and the voltage change curve in the time period from t0 to t1 are intercepted and imported into the matrix item corresponding to the virtual line point, and the abnormal extreme value of the abnormal curve is iterated in the matrix item to complete the data iteration of the distribution substation area model, and obtain the corresponding distribution substation area dynamic model.

[0031] Furthermore, the data analysis module analyzes the operating status of the dynamic model of the power distribution substation area, and the process of determining whether there is an abnormality in the power distribution status in the power distribution substation area includes:

[0032] According to the power parameters in the matrix items of each virtual line point in each virtual monitoring point in the dynamic model of the distribution station area, the first evaluation coefficient of the corresponding virtual monitoring point is obtained, which is recorded as Pg i ;

[0033] Set the monitoring point evaluation coefficient threshold interval (P0, P1);

[0034] When Pg i ∈(P0, P1), it means that the corresponding virtual monitoring point operates normally;

[0035] when When , it indicates that the operation of the corresponding virtual monitoring point is abnormal, and the line point matrix corresponding to the abnormal line point is marked;

[0036] According to the line point matrix corresponding to the abnormal line point, the line evaluation coefficient of the abnormal line point is obtained, which is recorded as Px j ;

[0037] Set the line evaluation coefficient threshold interval (X0, X1);

[0038] When Px j ∈(X0, X1), the abnormal line point is marked as a suspected fault line node, and a line node dispatch instruction is generated;

[0039] when , the virtual line between the virtual line points corresponding to the line point matrix is ​​marked as a suspected fault line, and a line scheduling instruction is generated.

[0040] Furthermore, the process in which the power distribution decision module performs power distribution scheduling on the power distribution substation according to the generated power distribution scheduling module includes:

[0041] When a line dispatch instruction is generated, the virtual line point connected to the suspected faulty line is marked, and the line node corresponding to the marked virtual line point is cut off, and the location of the suspected faulty line is sent to the control center, and the control center arranges technicians to check the suspected faulty line;

[0042] When a line node dispatch instruction is generated, a virtual line point corresponding to the abnormal line point in the dynamic model of the distribution station area is marked;

[0043] Obtain other line nodes that have the same load mark as the abnormal line point, obtain the load balance of other line nodes, and generate corresponding load adjustment plans based on the load demand of the abnormal line point and the load balance of each line node.

[0044] Furthermore, the generation process of the load adjustment scheme is as follows:

[0045] Sort the line nodes from high to low according to the load balance, and label the line nodes according to the sorting result, denoted as k, where k = 1, 2, ..., s, where s>0, and s is an integer;

[0046] According to the sorting results, the load balance of each line node is compared with the load demand in turn;

[0047] If the load balance of the line node with label k=1 is not less than the load demand, the line node is marked as a dispatching line node, and the temporary dispatch of the power load of the abnormal line point is completed through the dispatching line node;

[0048] If the load balance of the line node labeled k=1 is lower than the load demand, the sum of the load balances of the line nodes labeled k=1 and k=2 is compared with the load demand, and so on; finally, the temporary dispatch of the power load at the abnormal line point is completed.

[0049] Compared with the prior art, the beneficial effects of the present invention are: by real-time monitoring of the power data of each line node in each power node in the distribution station area, and building a dynamic model of the distribution station area based on the collected power data, and judging whether there are abnormalities in the operation of each power node and each line node in the power node, if there are abnormalities, a corresponding load adjustment plan is generated according to the abnormalities that have occurred, and the control center performs temporary power load scheduling according to the generated load adjustment plan, so that when an abnormality occurs in the distribution station area, a more reasonable and adaptive power scheduling plan can be given to reduce the impact of the abnormality. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0051] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0052] like Figure 1 As shown, an intelligent power distribution control system based on the Internet of Things includes a control center, and the control center is communicatively and / or electrically connected to a data acquisition module, a data processing module, a data analysis module, and a power distribution decision module;

[0053] The data acquisition module is composed of several data acquisition units and is used to collect power data of each monitoring node in the distribution station area;

[0054] The data processing module is used to construct a distribution substation area model, and update the distribution substation area model according to the collected power data to obtain a distribution substation area dynamic model;

[0055] The data analysis module is used to analyze the operating status of the dynamic model of the power distribution area, determine whether there is any abnormality in the power distribution status in the power distribution area, and if there is any abnormality, generate a power distribution dispatch instruction;

[0056] The power distribution decision module is used to perform power distribution scheduling on the power distribution station area according to the generated power distribution scheduling module.

[0057] It should be further explained that, in the specific implementation process, a number of power nodes are set in the distribution station area, each power node is used as a monitoring node, and a data acquisition unit is set in each monitoring node;

[0058] Several distribution lines are arranged between each power node, and line nodes that are the same in number as the distribution lines are arranged in the monitoring node, and each line node is associated with a distribution line;

[0059] The data acquisition unit collects the power data of the monitoring node and each line node in the monitoring node in real time, and the power data includes current value and voltage value.

[0060] It should be further explained that, in the specific implementation process, the process of the data processing module constructing the distribution station area model includes:

[0061] Construct a two-dimensional plane coordinate system, and generate virtual monitoring points corresponding to each monitoring node in the two-dimensional plane coordinate system;

[0062] Setting a virtual line point for the virtual monitoring point, each virtual line point being associated with a line node, and setting a line state for each virtual line point, the line state including a normal state and an abnormal state;

[0063] Each virtual monitoring point is labeled as i, where i=1, 2, ..., n, n is an integer, and n>0;

[0064] Setting a load mark for the virtual line point according to the type of the line node associated with the virtual line point in each virtual monitoring point, wherein the load mark includes an input load mark and an output load mark;

[0065] Generate a corresponding virtual line at a corresponding virtual line point according to the distribution line between the monitoring nodes, and set a line type label for the virtual line according to the load mark of the virtual line point connected to the virtual line, wherein the line type label includes an input line label and an output line label;

[0066] Generate a corresponding line point matrix according to two virtual line points connected by the virtual line, the line point matrix including two matrix items, and associate the generated line point matrix with the virtual line;

[0067] The line point matrix associated with each virtual line in the virtual monitoring point labeled i is labeled as j, where j=1, 2, ..., m, m is an integer, and m>0;

[0068] The line point matrix labeled j is recorded as [XsD j ,XcD j ] T i , among which, XsD j The matrix item representing the virtual route point numbered j within the virtual monitoring point numbered i, XcD j represents a matrix entry of a virtual line point in another virtual monitoring point connected to the virtual line point through a virtual line, T represents a matrix class value, and depends on XsD j The load mark of the corresponding virtual line point;

[0069] Construct a data transmission link, through which the matrix items are connected to the data acquisition units of the corresponding line nodes for communication, thereby completing the construction of the distribution station area model;

[0070] Through the data transmission link, the power data obtained by each data acquisition unit is imported into the corresponding matrix item, thereby completing the data update of the distribution station area model and obtaining the dynamic model of the distribution station area.

[0071] It should be further explained that, in the specific implementation process, the data processing module updates the distribution substation area model according to the collected power data, and the process of obtaining the distribution substation area dynamic model includes:

[0072] Construct a two-dimensional coordinate system of time with respect to current value and voltage value;

[0073] Generate corresponding current change curves and voltage change curves from the power data obtained by each data acquisition unit;

[0074] Mapping the generated current change curve and voltage change curve into a two-dimensional coordinate system to obtain a power parameter change graph;

[0075] The voltage threshold interval and the current threshold interval are set in the power parameter variation diagram, and are denoted as (D1 u j , D2u j ) and (A1t j , A2t j );

[0076] Set the data update cycle T;

[0077] The initial time is recorded as t0, the current time is recorded as t1, and the interval from t0 to t1 is recorded as t;

[0078] Mark the current change curve and voltage change curve between time t0 and time t1;

[0079] When t<T, and the voltage change curve and the current change curve corresponding to the time t1 are within the corresponding voltage threshold interval and current threshold interval, then at t=T, the line state corresponding to the virtual line point is updated to a normal state, and the current change curve and the voltage change curve in the time period from t0 to t1 are intercepted and imported into the matrix item corresponding to the virtual line point, and the corresponding current standard value and voltage standard value are generated, and the current standard value and the voltage standard value are the current average value and the voltage average value in the time period from t0 to t1;

[0080] By iterating the generated current standard value and voltage standard value in the matrix item, the data iteration of the distribution substation area model is completed, and the corresponding distribution substation area dynamic model is obtained;

[0081] It should be further explained that, in the specific implementation process, when t=T, t0 is reset so that t0=t1, and the data update cycle T is reset, and the reasoning is based on this;

[0082] When t<T, and there is any curve in the voltage change curve and the current change curve corresponding to the time t1 that is not within the corresponding voltage threshold interval and current threshold interval, the corresponding change curve is marked as an abnormal curve, and when t=T, the virtual line point corresponding to the abnormal curve is marked as an abnormal line point, the current change curve and the voltage change curve in the time period from t0 to t1 are intercepted, imported into the matrix item corresponding to the virtual line point, and the abnormal extreme values ​​of the abnormal curve are iterated in the matrix item to complete the data iteration of the distribution station area model, and the corresponding is obtained, thereby obtaining the corresponding distribution station area dynamic model; it should be further explained that, in the specific implementation process, the abnormal extreme values ​​are the peak values ​​and valley values ​​in the data in the abnormal curve that are not within the corresponding threshold interval.

[0083] It should be further explained that, in the specific implementation process, the data analysis module analyzes the operating status of the dynamic model of the power distribution area, and the process of determining whether there is an abnormality in the power distribution state in the power distribution area includes:

[0084] According to the power parameters in the matrix items of each virtual line point in each virtual monitoring point in the dynamic model of the distribution station area, the first evaluation coefficient of the corresponding virtual monitoring point is obtained, and the first evaluation coefficient of the virtual monitoring point labeled i is recorded as Pg i ;

[0085] in,

[0086] Among them, I j is the current value from t0 to t1, U j is the voltage value from t0 to t1;

[0087] Set the monitoring point evaluation coefficient threshold interval (P0, P1);

[0088] When Pg i ∈(P0, P1), it means that the corresponding virtual monitoring point operates normally;

[0089] when When , it indicates that the operation of the corresponding virtual monitoring point is abnormal, and the line point matrix corresponding to the abnormal line point is marked;

[0090] According to the line point matrix corresponding to the abnormal line point, the line evaluation coefficient of the abnormal line point is obtained, which is recorded as Px j ;

[0091] in,

[0092] Among them, [K] T is the line transmission loss coefficient, which depends on XsD j Corresponding load mark; [XsD j ] and [XcD j ] are the power data of the corresponding abnormal line points;

[0093] Set the line evaluation coefficient threshold interval (X0, X1);

[0094] When Px j ∈(X0, X1), the abnormal line point is marked as a suspected fault line node, and a line node dispatch instruction is generated;

[0095] when , the virtual line between the virtual line points corresponding to the line point matrix is ​​marked as a suspected fault line, and a line scheduling instruction is generated.

[0096] It should be further explained that, in the specific implementation process, the process in which the power distribution decision module performs power distribution scheduling on the power distribution substation according to the generated power distribution scheduling module includes:

[0097] When a line dispatch instruction is generated, the virtual line point connected to the suspected faulty line is marked, and the line node corresponding to the marked virtual line point is cut off, and the location of the suspected faulty line is sent to the control center, and the control center arranges technicians to check the suspected faulty line;

[0098] When a line node dispatch instruction is generated, a virtual line point corresponding to the abnormal line point in the dynamic model of the distribution station area is marked;

[0099] Obtain other line nodes that have the same load mark as the abnormal line point, obtain the load balance of other line nodes, and generate corresponding load adjustment plans based on the load demand of the abnormal line point and the load balance of each line node. The specific process is as follows:

[0100] The load demand at the abnormal line point is recorded as Fx;

[0101] Mark the other line nodes that have the same load mark as the abnormal line point, obtain the load balance of each line node, sort the line nodes from high to low according to the load balance, and label the line nodes according to the sorting result, denoted as k, where k = 1, 2, ..., s, where s>0, and s is an integer;

[0102] The load balance of the line node labeled k is recorded as Fz k ; It should be further explained that, in the specific implementation process, the load balance is the difference between the current power data of the line node and the upper limit value of the corresponding voltage threshold interval and current threshold interval;

[0103] According to the sorting results, the load balance of each line node is compared with the load demand in turn;

[0104] If the load balance of the line node with label k=1 is not less than the load demand, the line node is marked as a dispatching line node, and the temporary dispatch of the power load of the abnormal line point is completed through the dispatching line node;

[0105] If the load balance of the line node with label k=1 is lower than the load demand, the sum of the load balances of the line nodes with label k=1 and k=2 is compared with the load demand, and so on; finally, the temporary dispatch of the power load of the abnormal line point is completed;

[0106] It should be further explained that, in the specific implementation process, if the sum of the load balances of all line nodes is lower than the load demand, a manual adjustment request is sent to the control center, and the control center manually dispatches the power load to the abnormal line point based on the manual adjustment request.

[0107] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent power distribution control system based on the Internet of Things, comprising a control center, characterized in that: The control center is communicatively and / or electrically connected to a data acquisition module, a data processing module, a data analysis module and a power distribution decision module; The data acquisition module is composed of several data acquisition units and is used to collect power data of each monitoring node in the distribution station area; The data processing module is used to construct a distribution substation area model, and update the distribution substation area model according to the collected power data to obtain a distribution substation area dynamic model; The data analysis module is used to analyze the operating status of the dynamic model of the power distribution area, determine whether there is any abnormality in the power distribution status in the power distribution area, and if there is any abnormality, generate a power distribution dispatch instruction; The power distribution decision module is used to perform power distribution scheduling for the distribution station area according to the generated power distribution scheduling module; A plurality of power nodes are arranged in the distribution station area, each power node is used as a monitoring node, and a data acquisition unit is arranged at each monitoring node; Several distribution lines are arranged between each power node, and line nodes that are the same in number as the distribution lines are arranged in the monitoring node, and each line node is associated with a distribution line; The data acquisition unit collects power data of the monitoring node and each line node in the monitoring node in real time, wherein the power data includes current value and voltage value; The process of constructing the distribution station area model by the data processing module includes: Construct a two-dimensional plane coordinate system, and generate virtual monitoring points corresponding to each monitoring node in the two-dimensional plane coordinate system; Setting a virtual line point for the virtual monitoring point, each virtual line point being associated with a line node, and setting a line state for each virtual line point, the line state including a normal state and an abnormal state; Setting a load mark for the virtual line point according to the type of the line node associated with the virtual line point in each virtual monitoring point, wherein the load mark includes an input load mark and an output load mark; Generate a corresponding virtual line at a corresponding virtual line point according to the distribution line between the monitoring nodes, and set a line type label for the virtual line according to the load mark of the virtual line point connected to the virtual line, wherein the line type label includes an input line label and an output line label; Generate a corresponding line point matrix according to two virtual line points connected by the virtual line, the line point matrix including two matrix items, and associate the generated line point matrix with the virtual line; A data transmission link is constructed, and the matrix items are communicatively connected with the data acquisition units of the corresponding line nodes through the data transmission link, thereby completing the construction of the distribution station area model.

2. According to the Internet of Things-based intelligent power distribution control system of claim 1, it is characterized in that: The data processing module updates the distribution substation area model according to the collected power data, and the process of obtaining the distribution substation area dynamic model includes: Constructing a two-dimensional coordinate system of current value and voltage value in time, mapping each and into the two-dimensional coordinate system, obtaining a power parameter variation diagram, and setting a voltage threshold interval and a current threshold interval in the power parameter variation diagram; Set the data update cycle T; The initial time is recorded as t0, the current time is recorded as t1, and the interval from t0 to t1 is recorded as t; Mark the current change curve and voltage change curve between time t0 and time t1; When t<T, and the voltage change curve and the current change curve corresponding to the time t1 are within the corresponding voltage threshold interval and current threshold interval, then at t=T, the line state corresponding to the virtual line point is updated to a normal state, and the current change curve and the voltage change curve in the time period from t0 to t1 are intercepted and imported into the matrix item corresponding to the virtual line point, and the corresponding current standard value and voltage standard value are generated; By iterating the generated current standard value and voltage standard value in the matrix item, the data iteration of the distribution substation area model is completed, and the corresponding distribution substation area dynamic model is obtained.

3. The intelligent power distribution control system based on the Internet of Things according to claim 2 is characterized in that: When t<T, and any of the voltage change curve and the current change curve corresponding to time t1 is not within the corresponding voltage threshold interval and current threshold interval, the corresponding change curve is marked as an abnormal curve, and when t=T, the virtual line point corresponding to the abnormal curve is marked as an abnormal line point, the current change curve and the voltage change curve in the time period from t0 to t1 are intercepted and imported into the matrix item corresponding to the virtual line point, and the abnormal extreme value of the abnormal curve is iterated in the matrix item to complete the data iteration of the distribution substation model, and obtain the corresponding distribution substation dynamic model.

4. The intelligent power distribution control system based on the Internet of Things according to claim 3 is characterized in that: The data analysis module analyzes the operating status of the dynamic model of the power distribution area to determine whether there is an abnormality in the power distribution state in the power distribution area. The process includes: According to the power parameters in the matrix items of each virtual line point in each virtual monitoring point in the dynamic model of the distribution station area, the first evaluation coefficient of the corresponding virtual monitoring point is obtained, which is recorded as Pg i ; Set the monitoring point evaluation coefficient threshold interval (P0, P1); When Pg i ∈ (P0, P1), it means that the corresponding virtual monitoring point operates normally; When Pg i ∉(P0, P1), it means that the operation of the corresponding virtual monitoring point is abnormal, and the line point matrix corresponding to the abnormal line point is marked; According to the line point matrix corresponding to the abnormal line point, the line evaluation coefficient of the abnormal line point is obtained, which is recorded as Px j ; Set the line evaluation coefficient threshold interval (X0, X1); When Px j ∈(X0,X1), the abnormal line point is marked as a suspected fault line node, and a line node dispatch instruction is generated; When Px j ∉(X0, X1), the virtual line between the virtual line points corresponding to the line point matrix is ​​marked as a suspected fault line, and a line scheduling instruction is generated.

5. The intelligent power distribution control system based on the Internet of Things according to claim 4 is characterized in that: The process of the power distribution decision module performing power distribution scheduling on the power distribution substation according to the generated power distribution scheduling module includes: When a line dispatch instruction is generated, the virtual line point connected to the suspected faulty line is marked, and the line node corresponding to the marked virtual line point is cut off, and the location of the suspected faulty line is sent to the control center, and the control center arranges technicians to check the suspected faulty line; When a line node dispatch instruction is generated, a virtual line point corresponding to the abnormal line point in the dynamic model of the distribution station area is marked; Obtain other line nodes that have the same load mark as the abnormal line point, obtain the load balance of other line nodes, and generate corresponding load adjustment plans based on the load demand of the abnormal line point and the load balance of each line node.

6. The intelligent power distribution control system based on the Internet of Things according to claim 5 is characterized in that: The generation process of the load adjustment scheme is as follows: Sort the line nodes from high to low according to the load balance; According to the sorting results, the load balance of each line node is compared with the load demand in turn; If the load balance of the line node is not less than the load demand, the line node is marked as a dispatching line node, and the temporary dispatch of the power load of the abnormal line point is completed through the dispatching line node; If the load balance of a line node is lower than the load demand, the sum of the load balances of the first two line nodes is compared with the load demand, and so on; finally, the temporary dispatch of the power load at the abnormal line point is completed.

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