Online optimization method and system for special transformer

Abstract

The invention discloses an online optimization method and system for a special transformer. All-weather detection is carried out based on a working part; and matching a corresponding load schematic diagram according to the load parameters corresponding to the working part, determining a plurality of corresponding abnormal parts based on the load schematic diagram, and defining abnormal factors according to the plurality of abnormal parts and the corresponding abnormal positions. In the abnormal management and control logic, the part to be influenced is defined for the abnormal factors and the work function of the working part, so that targeted management and control can be carried out according to the part to be influenced, the abnormal power utilization event is clear, and whether the abnormal power utilization user is an electricity stealing user or not is judged according to the abnormal power utilization event. And meanwhile, path optimization is carried out according to a plurality of abnormal parts and the electricity stealing nodes, the power transmission path of the working part is optimized, interruption processing is carried out on the electricity stealing nodes, and online optimization is carried out on the working scene corresponding to the special transformer in time.

Description

Technical Field

[0001] The present invention relates to the technical field of special transformers, and in particular to an online optimization method and system for special transformers. Background Art

[0002] With the development of science and technology, industrial parks and factories and mines are booming, and the number of applications of special transformers (abbreviated as "special transformers") is large. The corresponding working parts are defined according to the working scenarios corresponding to the special transformers, and video monitoring is carried out for the working scenarios corresponding to the special transformers to prevent random wiring. However, video monitoring cannot carry out targeted control of the working parts. The working parts do not detect load parameters in real time during the working process, and cannot effectively locate electricity theft users, and cannot timely perform online optimization of the working scenarios corresponding to the special transformers. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides an online optimization method and system for a special transformer, which locates the working scene corresponding to the special transformer, and defines the corresponding working part according to the working scene corresponding to the special transformer; performs all-weather detection based on the working part, and collects the load parameters corresponding to the working part; matches the corresponding load schematic diagram according to the load parameters corresponding to the working part, and determines the corresponding multiple abnormal parts based on the load schematic diagram, thereby clarifying the multiple abnormal parts, so as to facilitate multi-dimensional control according to the load schematic diagram, and fully considers the matching of the load parameters corresponding to the working part.

[0004] Furthermore, abnormal factors are defined according to multiple abnormal parts and corresponding abnormal positions, and corresponding abnormal management and control logic is triggered according to the abnormal factors and the work functions of the working part; in the abnormal management and control logic, the affected part is defined according to the abnormal factors and the work functions of the working part, so as to facilitate targeted management according to the affected part, and clarify the abnormal power consumption events, so as to judge whether the abnormal power users are power theft users according to the abnormal power consumption events, and then further targeted processing is carried out on the power theft users. At the same time, path optimization is carried out according to multiple abnormal parts and power theft nodes, and the power transmission path of the working part is optimized, and the power theft nodes are interrupted to ensure the effective positioning of the power theft users, and timely online optimization of the working scenarios corresponding to the dedicated transformers.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides an online optimization method for a dedicated transformer, which is applied to an online optimization scenario of a dedicated transformer;

[0006] The online optimization method of the dedicated transformer comprises:

[0007] Locate the working scene corresponding to the dedicated transformer, and define the corresponding working parts according to the working scene corresponding to the dedicated transformer;

[0008] Conduct all-weather detection based on the working part and collect the load parameters corresponding to the working part;

[0009] Matching a corresponding load schematic diagram according to a load parameter corresponding to the working part, and determining a corresponding plurality of abnormal parts based on the load schematic diagram;

[0010] Define abnormal factors based on multiple abnormal parts and corresponding abnormal locations, and trigger corresponding abnormal control logic based on abnormal factors and work functions of the work parts;

[0011] In the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption events corresponding to the abnormal power users are defined based on the comparison between the affected part and the abnormal power users, and it is determined whether the abnormal power users are power stealers based on the abnormal power consumption events;

[0012] If the abnormal electricity user is an electricity theft user, the electricity theft path is defined based on the reverse tracing of the electricity theft user, the corresponding electricity theft node is defined according to the electricity theft path, the path is optimized according to multiple abnormal parts and electricity theft nodes, and the transmission path of the working part is optimized. At the same time, the electricity theft node is interrupted.

[0013] Optionally, the positioning of the working scene corresponding to the dedicated transformer and defining the corresponding working part according to the working scene corresponding to the dedicated transformer include:

[0014] Collect electricity consumption information of dedicated transformer;

[0015] Defining the location information of the dedicated transformer according to the power consumption information of the dedicated transformer;

[0016] Perform positioning detection based on the positioning information of the dedicated transformer and locate the working scene corresponding to the dedicated transformer;

[0017] A corresponding traversal method is matched based on the power consumption information of the dedicated transformer, a traversal of the working scene corresponding to the dedicated transformer is triggered based on the traversal method, and a corresponding working part is defined during the traversal process of the working scene corresponding to the dedicated transformer.

[0018] Optionally, the all-weather detection based on the working part and the collection of load parameters corresponding to the working part include:

[0019] Freeze the working part;

[0020] Build multiple detection nodes based on the working part, and perform all-weather detection in multiple detection nodes;

[0021] Defining sub-load parameters of each detection node based on all-weather detection of multiple detection nodes;

[0022] Defining load integration methods based on multiple sub-load parameters and corresponding locations;

[0023] Associate multiple sub-load parameters, corresponding functions of the work parts and load integration methods;

[0024] The load parameters corresponding to the working part are defined according to a plurality of sub-load parameters, the functions corresponding to the working part, and the load integration method.

[0025] Optionally, matching a corresponding load schematic diagram according to a load parameter corresponding to the working part, and determining a corresponding plurality of abnormal parts based on the load schematic diagram, includes:

[0026] Load parameters corresponding to the rated working part;

[0027] Collect multiple load parameters, and match corresponding load schematic diagrams according to the multiple load parameters and corresponding working time points;

[0028] Traverse the load diagram and divide it into multiple load areas according to the load diagram;

[0029] Defining abnormal intervals based on region identification of multiple load regions;

[0030] Multiple abnormal intervals are associated, and corresponding multiple abnormal parts are determined according to the multiple abnormal intervals, load schematic location, and various working parts.

[0031] Optionally, defining abnormal factors according to multiple abnormal parts and corresponding abnormal positions, and triggering corresponding abnormal management and control logic according to the abnormal factors and the work functions of the work parts, includes:

[0032] Freeze multiple abnormal parts and define the abnormal positions corresponding to the multiple abnormal parts;

[0033] defining an abnormal factor based on a plurality of abnormal parts and corresponding abnormal locations;

[0034] Associate abnormal factors with job functions of the job part;

[0035] The corresponding abnormal control logic is triggered according to the abnormal factors and the job functions of the work part. At this time, the corresponding abnormal coefficient is defined based on the abnormal factors and the job functions of the work part, and the corresponding abnormal control logic is defined according to the abnormal coefficient and the abnormal control comparison table.

[0036] Optionally, in the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption event corresponding to the abnormal power user is defined according to the comparison between the affected part and the abnormal power user, and whether the abnormal power user is a power theft user is determined according to the abnormal power consumption event, including:

[0037] In the abnormal control logic, define the affected part according to the abnormal factors and the work functions of the work part;

[0038] Freeze the part to be affected, and define the corresponding time to be affected based on the reverse tracing of the part to be affected;

[0039] Locate multiple electricity users associated with the dedicated transformer, and associate the multiple electricity users with the time to be affected.

[0040] Optionally, in the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption event corresponding to the abnormal power user is defined according to the comparison between the affected part and the abnormal power user, and whether the abnormal power user is a power theft user is determined according to the abnormal power consumption event, further comprising:

[0041] Real-time collection of electricity consumption parameters of multiple electricity users during the time to be affected;

[0042] Constructing a corresponding power consumption diagram according to power consumption parameters of multiple power users at the time to be affected, and defining abnormal power users based on the multiple power users and the corresponding power consumption diagrams;

[0043] Defining abnormal power consumption events corresponding to abnormal power users based on the comparison between the part to be affected and the abnormal power users;

[0044] Determine whether the abnormal electricity user is an electricity theft user based on abnormal electricity consumption events.

[0045] Optionally, if the abnormal electricity user is an electricity theft user, an electricity theft path is defined based on the reverse tracing of the electricity theft user, a corresponding electricity theft node is defined according to the electricity theft path, the path is optimized according to multiple abnormal parts and electricity theft nodes, and the power transmission path of the working part is optimized, and at the same time, the electricity theft node is interrupted, including:

[0046] Identify abnormal power consumption events and define excessive power consumption types based on the identification of abnormal power consumption events;

[0047] Electricity stealing users are defined based on the types of excessive electricity consumption, electricity operation scenarios of abnormal electricity users, and previous electricity bills of abnormal electricity users.

[0048] Optionally, if the abnormal electricity user is an electricity theft user, an electricity theft path is defined based on the reverse tracing of the electricity theft user, a corresponding electricity theft node is defined according to the electricity theft path, the path is optimized according to multiple abnormal parts and electricity theft nodes, and the power transmission path of the working part is optimized. At the same time, the electricity theft node is interrupted, and the method also includes:

[0049] If the abnormal electricity user is an electricity theft user, the electricity theft path is defined based on the reverse tracing of the electricity theft user;

[0050] Define corresponding electricity stealing nodes according to the electricity stealing path and the electricity consumption path of abnormal electricity users;

[0051] Optimize the route based on multiple abnormal parts and electricity theft nodes;

[0052] Optimize the path based on multiple abnormal parts and power stealing node outputs;

[0053] The transmission path of the working part is optimized according to the optimized path and the power consumption path of abnormal power users; at the same time, the power theft node is located and the power theft node is interrupted.

[0054] In addition, the embodiment of the present invention further provides an online optimization method and system for a dedicated transformer, wherein the precise bidirectional mutual matching system for personnel and positions includes:

[0055] A working module, used to locate the working scene corresponding to the dedicated transformer and define the corresponding working part according to the working scene corresponding to the dedicated transformer;

[0056] A collection module is used to perform all-weather detection based on the working part and collect the load parameters corresponding to the working part;

[0057] An abnormal module, used to match a corresponding load schematic diagram according to a load parameter corresponding to the working part, and determine a corresponding plurality of abnormal parts based on the load schematic diagram;

[0058] The exception control module is used to define the exception factors according to multiple exception parts and corresponding exception positions, and trigger the corresponding exception control logic according to the exception factors and the work functions of the work parts;

[0059] The judgment module is used to define the affected part according to the abnormal factors and the work functions of the work part in the abnormal control logic, and define the abnormal power consumption events corresponding to the abnormal power users according to the comparison between the affected part and the abnormal power users, and judge whether the abnormal power users are power stealers according to the abnormal power consumption events;

[0060] The path optimization module is used to define the electricity stealing path based on the reverse tracing of the electricity stealing user if the abnormal electricity user is the electricity stealing user, define the corresponding electricity stealing node according to the electricity stealing path, optimize the path according to multiple abnormal parts and electricity stealing nodes, optimize the transmission path of the working part, and at the same time, interrupt the electricity stealing node.

[0061] In an embodiment of the present invention, through the method in the embodiment of the present invention, the working scene corresponding to the dedicated transformer is located, and the corresponding working part is defined according to the working scene corresponding to the dedicated transformer; all-weather detection is performed based on the working part, and the load parameters corresponding to the working part are collected; the corresponding load schematic diagram is matched according to the load parameters corresponding to the working part, and the corresponding multiple abnormal parts are determined based on the load schematic diagram, so as to clarify the multiple abnormal parts, so as to facilitate multi-dimensional control according to the load schematic diagram, and fully consider the matching of the load parameters corresponding to the working part.

[0062] Furthermore, abnormal factors are defined according to multiple abnormal parts and corresponding abnormal positions, and corresponding abnormal management and control logic is triggered according to the abnormal factors and the work functions of the working part; in the abnormal management and control logic, the affected part is defined according to the abnormal factors and the work functions of the working part, so as to facilitate targeted management according to the affected part, and clarify the abnormal power consumption events, so as to judge whether the abnormal power users are power theft users according to the abnormal power consumption events, and then further targeted processing is carried out on the power theft users. At the same time, path optimization is carried out according to multiple abnormal parts and power theft nodes, and the power transmission path of the working part is optimized, and the power theft nodes are interrupted to ensure the effective positioning of the power theft users, and timely online optimization of the working scenarios corresponding to the dedicated transformers. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0064] Figure 1 1 is a flow chart of an online optimization method for a dedicated transformer in an embodiment of the present invention;

[0065] Figure 2 It is a schematic flow chart of S11 in the online optimization method for special transformer in the embodiment of the present invention;

[0066] Figure 3 It is a schematic flow chart of S12 in the online optimization method for special transformer in the embodiment of the present invention;

[0067] Figure 4 It is a schematic flow chart of S13 in the online optimization method for special transformer in the embodiment of the present invention;

[0068] Figure 5 It is a schematic flow chart of S14 in the online optimization method for special transformer in the embodiment of the present invention;

[0069] Figure 6 It is a schematic flow chart of S15 in the online optimization method for special transformer in the embodiment of the present invention;

[0070] Figure 7 It is a schematic flow chart of S16 in the online optimization method for dedicated transformer in an embodiment of the present invention;

[0071] Figure 8 It is a schematic diagram of the structure of the online optimization system for special transformer in the embodiment of the present invention;

[0072] Fig. 9 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0073] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] See also Figures 1 to 9 , an online optimization method for a dedicated transformer is applied to an online optimization scenario of a dedicated transformer; the online optimization method for a dedicated transformer includes:

[0075] Step S11: locating the working scene corresponding to the dedicated transformer, and defining the corresponding working part according to the working scene corresponding to the dedicated transformer;

[0076] Step S12: Perform all-weather detection based on the working part and collect load parameters corresponding to the working part;

[0077] Step S13: matching a corresponding load schematic diagram according to the load parameters corresponding to the working part, and determining corresponding multiple abnormal parts based on the load schematic diagram;

[0078] Step S14: defining abnormal factors according to the multiple abnormal parts and the corresponding abnormal positions, and triggering corresponding abnormal control logic according to the abnormal factors and the work functions of the work parts;

[0079] Step S15: In the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption events corresponding to the abnormal power users are defined according to the comparison between the affected part and the abnormal power users, and it is determined whether the abnormal power users are power stealers according to the abnormal power consumption events;

[0080] Step S16: If the abnormal electricity user is an electricity theft user, an electricity theft path is defined based on the reverse tracing of the electricity theft user, and corresponding electricity theft nodes are defined according to the electricity theft path. The path is optimized according to multiple abnormal parts and electricity theft nodes, and the transmission path of the working part is optimized. At the same time, the electricity theft nodes are interrupted.

[0081] In an embodiment of the present invention, through the method in the embodiment of the present invention, the working scene corresponding to the dedicated transformer is located, and the corresponding working part is defined according to the working scene corresponding to the dedicated transformer; all-weather detection is performed based on the working part, and the load parameters corresponding to the working part are collected; the corresponding load schematic diagram is matched according to the load parameters corresponding to the working part, and the corresponding multiple abnormal parts are determined based on the load schematic diagram, so as to clarify the multiple abnormal parts, so as to facilitate multi-dimensional control according to the load schematic diagram, and fully consider the matching of the load parameters corresponding to the working part.

[0082] Furthermore, abnormal factors are defined according to multiple abnormal parts and corresponding abnormal positions, and corresponding abnormal management and control logic is triggered according to the abnormal factors and the work functions of the working part; in the abnormal management and control logic, the affected part is defined according to the abnormal factors and the work functions of the working part, so as to facilitate targeted management according to the affected part, and clarify the abnormal power consumption events, so as to judge whether the abnormal power users are power theft users according to the abnormal power consumption events, and then further targeted processing is carried out on the power theft users. At the same time, path optimization is carried out according to multiple abnormal parts and power theft nodes, and the power transmission path of the working part is optimized, and the power theft nodes are interrupted to ensure the effective positioning of the power theft users, and timely online optimization of the working scenarios corresponding to the dedicated transformers.

[0083] refer to Figure 2 , in step S11, the working scene corresponding to the dedicated transformer is located, and the corresponding working part is defined according to the working scene corresponding to the dedicated transformer;

[0084] In the specific implementation process of the present invention, the specific steps may be:

[0085] S111: Collecting power consumption information of dedicated transformer;

[0086] S112: defining location information of the dedicated transformer according to the power consumption information of the dedicated transformer;

[0087] S113: Performing positioning detection based on the positioning information of the dedicated transformer, and locating the working scene corresponding to the dedicated transformer;

[0088] S114: Matching a corresponding traversal method based on the power consumption information of the dedicated transformer, triggering the traversal of the working scene corresponding to the dedicated transformer based on the traversal method, and defining a corresponding working part during the traversal process of the working scene corresponding to the dedicated transformer.

[0089] In the embodiment of the present application, the power consumption information of the dedicated transformer is collected, and information processing is performed on the power consumption information of the dedicated transformer, so as to define the positioning information of the dedicated transformer according to the power consumption information of the dedicated transformer, thereby introducing the positioning information of the dedicated transformer, and presenting the position of the dedicated transformer through the positioning information of the dedicated transformer. Optionally, the power consumption information of the dedicated transformer is information about the electrical part contained in the dedicated transformer, and the positioning information of the dedicated transformer is a part of the power consumption information of the dedicated transformer, and can be presented as positioning coordinates.

[0090] At this time, positioning detection is performed based on the positioning information of the dedicated transformer, and the working scene corresponding to the dedicated transformer is located, so that the working scene corresponding to the dedicated transformer is frozen in the positioning detection of the dedicated transformer, and the working scene corresponding to the dedicated transformer is introduced, so as to match the corresponding traversal method based on the power consumption information of the dedicated transformer, trigger the traversal of the working scene corresponding to the dedicated transformer based on the traversal method, and define the corresponding working part in the traversal process of the working scene corresponding to the dedicated transformer, so as to perform targeted traversal based on the traversal method, so as to control the corresponding work traversal during the traversal process. Optionally, the working scene corresponding to the dedicated transformer is used as the scene where the dedicated transformer is in a working state, and involves components such as the power supply room and current transmission line of the dedicated transformer. The traversal method includes overall traversal or partial traversal.

[0091] refer to Figure 3 , in step S12, all-weather detection is performed based on the working part, and load parameters corresponding to the working part are collected;

[0092] In the specific implementation process of the present invention, the specific steps may be:

[0093] S121: freeze working part;

[0094] S122: construct multiple detection nodes based on the working part, and perform all-weather detection in the multiple detection nodes;

[0095] S123: defining sub-load parameters of each detection node based on all-weather detection of multiple detection nodes;

[0096] S124: defining a load integration method according to a plurality of sub-load parameters and corresponding positions;

[0097] S125: Associating multiple sub-load parameters, functions corresponding to the working parts, and load integration methods;

[0098] S126: Defining load parameters corresponding to the working part according to the plurality of sub-load parameters, the functions corresponding to the working part, and the load integration method.

[0099] In an embodiment of the present application, the working part is frozen, and the working part is further controlled. At this time, multiple detection nodes are constructed based on the working part, and all-weather detection is performed in multiple detection nodes, so as to facilitate real-time control of multiple detection nodes, so as to define the sub-load parameters of each detection node based on the all-weather detection of multiple detection nodes, and introduce the sub-load parameters of each detection node to ensure the accuracy of the sub-load parameters of each detection node. Optionally, the working part, as a working component in the working scene corresponding to the dedicated transformer, can be a power supply component, a circuit transmission component and other components. The detection node, as a node that needs to be detected in the working part, can be a location where the current passes through the working part. The sub-load parameter is a part of the load parameter, as the current parameter, voltage parameter, etc. of the corresponding detection node.

[0100] At this time, the load integration method is defined according to multiple sub-load parameters and corresponding positions. The load integration method is controlled in multiple dimensions through multiple sub-load parameters and corresponding positions to ensure the accuracy of the load integration method and adapt to the integration of multiple sub-load parameters. Optionally, the load integration method as a method of integrating multiple sub-load parameters can be an average integration or an additive combination, which is not limited here.

[0101] Therefore, multiple sub-load parameters, the functions corresponding to the working part, and the load integration method are associated; the load parameters corresponding to the working part are defined according to the multiple sub-load parameters, the functions corresponding to the working part, and the load integration method, and the load parameters corresponding to the working part are controlled to ensure the accuracy of the load parameters corresponding to the working part. Optionally, the load parameter is an overall current parameter or voltage parameter of the working part.

[0102] refer to Figure 4 , in step S13, matching the corresponding load schematic diagram according to the load parameters corresponding to the working part, and determining the corresponding multiple abnormal parts based on the load schematic diagram;

[0103] In the specific implementation process of the present invention, the specific steps may be:

[0104] S131: load parameters corresponding to the fixed working part;

[0105] S132: Collect multiple load parameters, and match corresponding load schematic diagrams according to the multiple load parameters and corresponding working time points;

[0106] S133: traversing the load schematic diagram, and dividing the load schematic diagram into multiple load areas;

[0107] S134: defining an abnormal interval according to the region identification of the plurality of load regions;

[0108] S135: Associating the multiple abnormal intervals, and determining the corresponding multiple abnormal parts according to the multiple abnormal intervals, the load schematic diagram positioning and each working part.

[0109] In an embodiment of the present application, the working scenario corresponding to the dedicated transformer is located, and the corresponding working part is defined according to the working scenario corresponding to the dedicated transformer; all-weather detection is performed based on the working part, and the load parameters corresponding to the working part are collected; the corresponding load schematic diagram is matched according to the load parameters corresponding to the working part, and the corresponding multiple abnormal parts are determined based on the load schematic diagram, thereby clarifying the multiple abnormal parts to facilitate multi-dimensional control according to the load schematic diagram, and fully considering the matching of the load parameters corresponding to the working part.

[0110] At this time, the load parameters corresponding to the working part are frozen. At this time, multiple load parameters are collected, and the corresponding load schematic diagram is matched according to the multiple load parameters and the corresponding working time points, so as to construct the load schematic diagram, so as to further control the load schematic diagram.

[0111] Furthermore, the load diagram is traversed, and multiple load areas are divided according to the load diagram; abnormal intervals are defined according to the regional identification of multiple load areas, thereby introducing abnormal intervals, and multiple abnormal intervals are associated, and multiple corresponding abnormal parts are determined according to multiple abnormal intervals, load diagram positioning, and various working parts, thereby clarifying multiple abnormal parts and achieving overall control of multiple abnormal parts. Optionally, the load diagram is constructed by load parameters and corresponding working time points, with the vertical coordinate being the load parameter and the horizontal coordinate being the corresponding working time point; the load area is a part of the load diagram and is divided by the load diagram, the load area corresponds to the corresponding working part, and the abnormal interval is the interval in the abnormal load parameter.

[0112] refer to Figure 5 , S14: defining abnormal factors according to the multiple abnormal parts and the corresponding abnormal positions, and triggering corresponding abnormal control logic according to the abnormal factors and the work functions of the work parts;

[0113] In the specific implementation process of the present invention, the specific steps may be:

[0114] S141: freeze multiple abnormal parts, and define abnormal positions corresponding to the multiple abnormal parts;

[0115] S142: defining abnormal factors based on the multiple abnormal parts and the corresponding abnormal positions;

[0116] S143: Associated abnormal factors and job functions of the work part;

[0117] S144: triggering corresponding abnormal control logic according to abnormal factors and job functions of the work part. At this time, defining corresponding abnormal coefficients based on abnormal factors and job functions of the work part, and defining corresponding abnormal control logic according to abnormal coefficients and abnormal control comparison table.

[0118] In the embodiment of the present application, multiple abnormal parts are frozen and the abnormal positions corresponding to the multiple abnormal parts are defined, so as to introduce multiple abnormal parts and corresponding positions, thereby defining abnormal factors based on multiple abnormal parts and corresponding abnormal positions, realizing multi-dimensional control of abnormal factors and ensuring the accuracy of abnormal factors. Optionally, abnormal factors include current abnormality, voltage abnormality, component abnormality, etc., which are not limited here.

[0119] At this time, the abnormal factors and the work functions of the work part are associated, and multi-dimensional control is performed on the abnormal factors and the work functions of the work part, so as to trigger the corresponding abnormal management and control logic according to the abnormal factors and the work functions of the work part, so as to perform abnormal control based on the abnormal management and control logic. At this time, the corresponding abnormal coefficient is defined based on the abnormal factors and the work functions of the work part, and the corresponding abnormal management and control logic is defined according to the abnormal coefficient and the abnormal management and control comparison table.

[0120] refer to Figure 6 , S15: In the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption event corresponding to the abnormal power user is defined according to the comparison between the affected part and the abnormal power user, and whether the abnormal power user is a power theft user is determined according to the abnormal power consumption event;

[0121] In the specific implementation process of the present invention, the specific steps may be:

[0122] S151: In the abnormal control logic, define the affected part according to the abnormal factors and the work functions of the work part;

[0123] S152: freeze the part to be affected, and define the corresponding time to be affected according to the reverse tracing of the part to be affected;

[0124] S153: locating multiple electricity users associated with the dedicated transformer, and associating the multiple electricity users and the time to be affected;

[0125] S154: collecting power consumption parameters of multiple power users at the time to be affected in real time; constructing a corresponding power consumption diagram according to the power consumption parameters of the multiple power users at the time to be affected, and defining abnormal power users based on the multiple power users and the corresponding power consumption diagram;

[0126] S155: defining abnormal power consumption events corresponding to abnormal power users according to the comparison between the part to be affected and the abnormal power users;

[0127] S156: Determine whether the abnormal electricity user is an electricity theft user based on the abnormal electricity consumption event.

[0128] In an embodiment of the present application, in the abnormal control logic, the part to be affected is defined according to the abnormal factors and the work functions of the work part, so as to perform multi-dimensional control through the abnormal factors and the work functions of the work part to ensure the accuracy of the part to be affected.

[0129] At this time, the affected part is fixed, and the corresponding affected time is defined according to the reverse tracing of the affected part, so as to clarify the affected time, thereby introducing the affected time, and then controlling the affected time. Optionally, the affected part is used as the part that may be affected. The affected time is used as the occurrence time corresponding to the affected part.

[0130] Therefore, multiple electricity users associated with the dedicated transformer are located, and the multiple electricity users and the time to be affected are associated; the electricity usage parameters of the multiple electricity users at the time to be affected are collected in real time; corresponding electricity usage schematic diagrams are constructed according to the electricity usage parameters of the multiple electricity users at the time to be affected, and abnormal electricity users are defined based on the multiple electricity users and the corresponding electricity usage schematic diagrams, so as to facilitate overall control through multiple electricity users and the corresponding electricity usage schematic diagrams, thereby freezing the abnormal electricity users and realizing the identification of abnormal electricity users.

[0131] Furthermore, the abnormal power consumption event corresponding to the abnormal power user is defined based on the comparison between the part to be affected and the abnormal power user; and whether the abnormal power user is a power theft user is determined based on the abnormal power consumption event, thereby realizing the determination of the power theft user. Optionally, the power theft user is a user who steals electricity. The abnormal power consumption event is an event with abnormal power consumption, which can be a power theft event or a high load event, and is not limited here.

[0132] refer to Figure 7 , S16: If the abnormal electricity user is an electricity theft user, then based on the reverse tracing of the electricity theft user, define the electricity theft path, define the corresponding electricity theft node according to the electricity theft path, optimize the path according to multiple abnormal parts and electricity theft nodes, and optimize the transmission path of the working part, and at the same time, interrupt the electricity theft node;

[0133] In the specific implementation process of the present invention, the specific steps may be:

[0134] S161: Frame the abnormal power consumption event, and define the excessive power consumption type according to the identification of the abnormal power consumption event;

[0135] S162: defining electricity stealing users based on excessive electricity usage types, electricity usage scenarios of abnormal electricity users, and previous electricity bills of abnormal electricity users;

[0136] S163: If the abnormal electricity user is an electricity theft user, define an electricity theft path based on reverse tracing of the electricity theft user;

[0137] S164: defining a corresponding power-stealing node according to the power-stealing path and the power-using path of the abnormal power user;

[0138] S165: Optimizing the path according to multiple abnormal parts and electricity stealing nodes;

[0139] S166: Outputting an optimized path based on multiple abnormal parts and power stealing nodes;

[0140] S167: The transmission path of the working part is optimized according to the optimized path and the power consumption path of the abnormal power user; at the same time, the power theft node is located and the power theft node is interrupted.

[0141] In the specific implementation process of the present invention, abnormal factors are defined according to multiple abnormal parts and corresponding abnormal positions, and corresponding abnormal control logic is triggered according to abnormal factors and the work functions of the working part; in the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the working part, so as to facilitate targeted control according to the affected part, and clarify the abnormal power consumption event, so as to judge whether the abnormal power user is a power theft user according to the abnormal power consumption event, and then further targeted treatment is carried out for the power theft user, at the same time, path optimization is carried out according to multiple abnormal parts and power theft nodes, and the power transmission path of the working part is optimized, and the power theft node is interrupted, so as to ensure the effective positioning of the power theft user, and timely online optimization of the work scene corresponding to the dedicated transformer. Optionally, the abnormal control logic serves as the logic for controlling abnormal factors.

[0142] At this time, the abnormal electricity consumption event is frozen, and the excessive electricity consumption type is defined based on the identification of the abnormal electricity consumption event, so as to introduce the excessive electricity consumption type and further control the excessive electricity consumption type. Therefore, the electricity theft user is defined based on the excessive electricity consumption type, the electricity usage scenario of the abnormal electricity user and the previous electricity bills of the abnormal electricity user, thereby realizing the identification of the electricity theft user.

[0143] Therefore, if the abnormal electricity user is an electricity theft user, the electricity theft path is defined based on the reverse tracing of the electricity theft user; the corresponding electricity theft node is defined according to the electricity theft path and the electricity consumption path of the abnormal electricity user; the path is optimized according to multiple abnormal parts and electricity theft nodes; the optimized path is output based on multiple abnormal parts and electricity theft nodes, and the electricity theft nodes are interrupted to ensure the effective positioning of the electricity theft user, and the working scene corresponding to the dedicated transformer is optimized online in time. In addition, the electricity theft node is located and the electricity theft node is interrupted to ensure the effective positioning of the electricity theft user, and the working scene corresponding to the dedicated transformer is optimized online in time. Optionally, the electricity theft path is used as the path for stealing electricity, and the optimized path refers to the optimized path.

[0144] Specific:

[0145] Multiple sensing units are installed on overhead lines respectively. They acquire current data through induction, calculate on-site, and send the data to the operation terminal through the micro-electric module in the sensing unit. The acquired data can be displayed and analyzed by accessing the operation terminal.

[0146] In an embodiment of the present invention, through the method in the embodiment of the present invention, the working scene corresponding to the dedicated transformer is located, and the corresponding working part is defined according to the working scene corresponding to the dedicated transformer; all-weather detection is performed based on the working part, and the load parameters corresponding to the working part are collected; the corresponding load schematic diagram is matched according to the load parameters corresponding to the working part, and the corresponding multiple abnormal parts are determined based on the load schematic diagram, so as to clarify the multiple abnormal parts, so as to facilitate multi-dimensional control according to the load schematic diagram, and fully consider the matching of the load parameters corresponding to the working part.

[0147] Furthermore, abnormal factors are defined according to multiple abnormal parts and corresponding abnormal positions, and corresponding abnormal management and control logic is triggered according to the abnormal factors and the work functions of the working part; in the abnormal management and control logic, the affected part is defined according to the abnormal factors and the work functions of the working part, so as to facilitate targeted management according to the affected part, and clarify the abnormal power consumption events, so as to judge whether the abnormal power users are power theft users according to the abnormal power consumption events, and then further targeted processing is carried out on the power theft users. At the same time, path optimization is carried out according to multiple abnormal parts and power theft nodes, and the power transmission path of the working part is optimized, and the power theft nodes are interrupted to ensure the effective positioning of the power theft users, and timely online optimization of the working scenarios corresponding to the dedicated transformers.

[0148] See also Figure 8 , Figure 8 It is a schematic diagram of the structural composition of the online optimization system for special transformer in the embodiment of the present invention.

[0149] like Figure 8 As shown, a dedicated transformer online optimization system, the precise bidirectional matching system for personnel positions includes:

[0150] A working module 21 is used to locate the working scene corresponding to the dedicated transformer and define the corresponding working part according to the working scene corresponding to the dedicated transformer;

[0151] The acquisition module 22 is used to perform all-weather detection based on the working part and collect the load parameters corresponding to the working part;

[0152] An abnormal module 23, used to match a corresponding load schematic diagram according to a load parameter corresponding to the working part, and determine a corresponding plurality of abnormal parts based on the load schematic diagram;

[0153] The abnormality control module 24 is used to define abnormal factors according to the multiple abnormal parts and the corresponding abnormal positions, and trigger the corresponding abnormality control logic according to the abnormal factors and the work functions of the work parts;

[0154] The judgment module 25 is used to define the affected part according to the abnormal factors and the work functions of the work part in the abnormal control logic, and define the abnormal power consumption event corresponding to the abnormal power user according to the comparison between the affected part and the abnormal power user, and judge whether the abnormal power user is a power theft user according to the abnormal power consumption event;

[0155] The path optimization module 26 is used to define a power-stealing path based on the reverse tracing of the power-stealing user if the abnormal power user is a power-stealing user, define a corresponding power-stealing node according to the power-stealing path, optimize the path according to multiple abnormal parts and power-stealing nodes, optimize the power transmission path of the working part, and interrupt the power-stealing node.

[0156] See also Fig. 9 , refer to the following Fig. 9 The electronic device 40 according to this embodiment of the present invention will be described. Fig. 9 The electronic device 40 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0157] like Fig. 9 As shown, the electronic device 40 is in the form of a general computing device. The components of the electronic device 40 may include but are not limited to: at least one processing unit 41, at least one storage unit 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).

[0158] The storage unit stores program codes, which can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.

[0159] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0160] The storage unit 42 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0161] Bus 43 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0162] The electronic device 40 may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 40, and / or any device that enables the electronic device 40 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 44. Furthermore, the electronic device 40 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 45. Fig. 9 As shown, the network adapter 45 communicates with other modules of the electronic device 40 via the bus 43. It should be understood that although Fig. 9 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup planning systems.

[0163] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0164] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. In addition, it stores computer program instructions, and when the computer program instructions are executed by a computer, the computer executes the above method.

[0165] In addition, the above describes in detail the online optimization system and system for the dedicated transformer provided in the embodiments of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for online optimization of a special transformer, characterized in that: Applicable to online optimization scenarios of dedicated transformers; The online optimization method of the dedicated transformer comprises: Locate the working scene corresponding to the dedicated transformer, and define the corresponding working parts according to the working scene corresponding to the dedicated transformer; Conduct all-weather detection based on the working part and collect the load parameters corresponding to the working part; Matching a corresponding load schematic diagram according to a load parameter corresponding to the working part, and determining a corresponding plurality of abnormal parts based on the load schematic diagram; Define abnormal factors based on multiple abnormal parts and corresponding abnormal locations, and trigger corresponding abnormal control logic based on abnormal factors and work functions of the work parts; In the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption events corresponding to the abnormal power users are defined based on the comparison between the affected part and the abnormal power users, and it is determined whether the abnormal power users are power stealers based on the abnormal power consumption events; If the abnormal electricity user is an electricity theft user, the electricity theft path is defined based on the reverse tracing of the electricity theft user, the corresponding electricity theft node is defined according to the electricity theft path, the path is optimized according to multiple abnormal parts and electricity theft nodes, and the transmission path of the working part is optimized. At the same time, the electricity theft node is interrupted.

2. The online optimization method for dedicated transformer according to claim 1, characterized in that: The positioning of the working scene corresponding to the dedicated transformer and defining the corresponding working part according to the working scene corresponding to the dedicated transformer include: Collect electricity consumption information of dedicated transformer; Defining the location information of the dedicated transformer according to the power consumption information of the dedicated transformer; Perform positioning detection based on the positioning information of the dedicated transformer and locate the working scene corresponding to the dedicated transformer; A corresponding traversal method is matched based on the power consumption information of the dedicated transformer, a traversal of the working scene corresponding to the dedicated transformer is triggered based on the traversal method, and a corresponding working part is defined during the traversal process of the working scene corresponding to the dedicated transformer.

3. The online optimization method for dedicated transformer according to claim 2, characterized in that: The all-weather detection based on the working part and the collection of load parameters corresponding to the working part include: Freeze work part; Build multiple detection nodes based on the working part, and perform all-weather detection in multiple detection nodes; Defining sub-load parameters of each detection node based on all-weather detection of multiple detection nodes; Defining load integration methods based on multiple sub-load parameters and corresponding locations; Associate multiple sub-load parameters, corresponding functions of the work parts and load integration methods; The load parameters corresponding to the working part are defined according to a plurality of sub-load parameters, the functions corresponding to the working part, and the load integration method.

4. The online optimization method for dedicated transformer according to claim 3 is characterized in that: The matching of the corresponding load schematic diagram according to the load parameter corresponding to the working part and determining the corresponding multiple abnormal parts based on the load schematic diagram include: Load parameters corresponding to the rated working part; Collect multiple load parameters, and match corresponding load schematic diagrams according to the multiple load parameters and corresponding working time points; Traverse the load diagram and divide it into multiple load areas according to the load diagram; Defining abnormal intervals based on region identification of multiple load regions; Multiple abnormal intervals are associated, and corresponding multiple abnormal parts are determined according to the multiple abnormal intervals, load schematic location, and various working parts.

5. The online optimization method for dedicated transformer according to claim 4, characterized in that: Defining abnormal factors according to multiple abnormal parts and corresponding abnormal positions, and triggering corresponding abnormal control logic according to the abnormal factors and the work functions of the work parts, includes: Freeze multiple abnormal parts and define the abnormal positions corresponding to the multiple abnormal parts; defining an abnormal factor based on a plurality of abnormal parts and corresponding abnormal locations; Associate abnormal factors with job functions of the job part; The corresponding abnormal control logic is triggered according to the abnormal factors and the job functions of the work part. At this time, the corresponding abnormal coefficient is defined based on the abnormal factors and the job functions of the work part, and the corresponding abnormal control logic is defined according to the abnormal coefficient and the abnormal control comparison table.

6. The online optimization method for dedicated transformer according to claim 5, characterized in that: In the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption event corresponding to the abnormal power user is defined according to the comparison between the affected part and the abnormal power user, and whether the abnormal power user is a power theft user is determined according to the abnormal power consumption event, including: In the abnormal control logic, define the affected part according to the abnormal factors and the work functions of the work part; Freeze the part to be affected, and define the corresponding time to be affected based on the reverse tracing of the part to be affected; Locate multiple electricity users associated with the dedicated transformer, and associate the multiple electricity users with the time to be affected.

7. The online optimization method for dedicated transformer according to claim 6, characterized in that: In the abnormal control logic, the affected part is defined according to the abnormal factors and the work functions of the work part, and the abnormal power consumption event corresponding to the abnormal power user is defined according to the comparison between the affected part and the abnormal power user, and whether the abnormal power user is a power theft user is determined according to the abnormal power consumption event, and further includes: Collecting electricity consumption parameters of multiple electricity users at the time to be affected in real time; constructing corresponding electricity consumption schematic diagrams according to the electricity consumption parameters of multiple electricity users at the time to be affected, and defining abnormal electricity users based on the multiple electricity users and the corresponding electricity consumption schematic diagrams; Defining abnormal power consumption events corresponding to abnormal power users based on the comparison between the part to be affected and the abnormal power users; Determine whether the abnormal electricity user is an electricity theft user based on abnormal electricity consumption events.

8. The online optimization method for dedicated transformer according to claim 7, characterized in that: If the abnormal electricity user is an electricity theft user, an electricity theft path is defined based on the reverse tracing of the electricity theft user, a corresponding electricity theft node is defined according to the electricity theft path, the path is optimized according to multiple abnormal parts and electricity theft nodes, and the transmission path of the working part is optimized. At the same time, the electricity theft node is interrupted, including: Identify abnormal power consumption events and define excessive power consumption types based on the identification of abnormal power consumption events; Electricity stealing users are defined based on the types of excessive electricity consumption, electricity operation scenarios of abnormal electricity users, and previous electricity bills of abnormal electricity users.

9. The online optimization method for dedicated transformer according to claim 8, characterized in that: If the abnormal electricity user is an electricity theft user, a power theft path is defined based on the reverse tracing of the electricity theft user, a corresponding power theft node is defined according to the power theft path, a path is optimized according to multiple abnormal parts and power theft nodes, and the power transmission path of the working part is optimized. At the same time, the power theft node is interrupted, and the method also includes: If the abnormal electricity user is an electricity theft user, the electricity theft path is defined based on the reverse tracing of the electricity theft user; Define corresponding electricity stealing nodes according to the electricity stealing path and the electricity consumption path of abnormal electricity users; Optimize the route based on multiple abnormal parts and electricity theft nodes; Optimize the path based on multiple abnormal parts and power stealing node outputs; The transmission path of the working part is optimized according to the optimized path and the power consumption path of abnormal power users; at the same time, the power theft node is located and the power theft node is interrupted.

10. A dedicated transformer online optimization system, characterized in that: The dedicated transformer online optimization system is applied to the dedicated transformer online optimization method as claimed in any one of claims 1 to 9, and the dedicated transformer online optimization system comprises: A working module, used to locate the working scene corresponding to the dedicated transformer and define the corresponding working part according to the working scene corresponding to the dedicated transformer; A collection module is used to perform all-weather detection based on the working part and collect the load parameters corresponding to the working part; An abnormal module, used to match a corresponding load schematic diagram according to a load parameter corresponding to the working part, and determine a corresponding plurality of abnormal parts based on the load schematic diagram; The exception control module is used to define the exception factors according to multiple exception parts and corresponding exception positions, and trigger the corresponding exception control logic according to the exception factors and the work functions of the work parts; The judgment module is used to define the affected part according to the abnormal factors and the work functions of the work part in the abnormal control logic, and define the abnormal power consumption events corresponding to the abnormal power users according to the comparison between the affected part and the abnormal power users, and judge whether the abnormal power users are power stealers according to the abnormal power consumption events; The path optimization module is used to define the electricity stealing path based on the reverse tracing of the electricity stealing user if the abnormal electricity user is the electricity stealing user, define the corresponding electricity stealing node according to the electricity stealing path, optimize the path according to multiple abnormal parts and electricity stealing nodes, optimize the transmission path of the working part, and at the same time, interrupt the electricity stealing node.

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