On-line optimization method and system for dedicated transformers

Abstract

The application discloses a kind of special variable voltage online optimization method and system, based on work part all-weather detection;According to the load parameter corresponding to work part Matching corresponding load schematic diagram, determine corresponding multiple abnormal parts based on load schematic diagram, define abnormal factor according to multiple abnormal parts and corresponding abnormal position.In abnormal control logic, for abnormal factor and the work function of work part Define to be affected part, in order to be affected part is controlled according to, and to abnormal power use event is clear, to determine whether abnormal power use user is electricity stealing user according to abnormal power use event, and then further targeted processing is carried out to electricity stealing user, simultaneously, according to multiple abnormal parts and electricity stealing node Path optimization is carried out, and the transmission path of work part is optimized, and the work scene corresponding to special variable voltage is interrupted to the processing of electricity stealing node in time, and online optimization is carried out.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of special transformer, in particular to an online optimization method and system of special transformer. BACKGROUND

[0002] With the development of science and technology, industrial parks and mines are booming, and the number of special transformers (referred to as "special transformers") is large. According to the definition of the corresponding work part corresponding to the working scene of the special transformer, the video monitoring is carried out for the working scene corresponding to the special transformer, and the line is prevented from being randomly connected. However, the video monitoring cannot be controlled for the work part, the load parameter is not detected in real time during the work process, the electricity stealing user cannot be effectively positioned, and the working scene corresponding to the special transformer cannot be timely optimized online. SUMMARY

[0003] The purpose of the present application is to overcome the shortcomings of the prior art, and the present application provides an online optimization method and system of special transformer, which positions the working scene corresponding to the special transformer, and defines the corresponding work part according to the working scene corresponding to the special transformer. Based on the work part, all-weather detection is carried out, and the load parameter corresponding to the work part is collected. According to the load parameter corresponding to the work part, the corresponding load schematic diagram is matched, and the corresponding multiple abnormal parts are determined based on the load schematic diagram, so as to be clear to the multiple abnormal parts, so as to control the multiple dimensions according to the load schematic diagram, and fully consider the matching condition of the load parameter corresponding to the work part.

[0004] Further, according to the multiple abnormal parts and the corresponding abnormal position, the abnormal factor is defined, and the abnormal control logic is triggered according to the abnormal factor and the work function of the work part. In the abnormal control logic, the affected part is defined according to the abnormal factor and the work function of the work part, so as to be clear to the abnormal power consumption event, so as to determine whether the abnormal power consumption user is a electricity stealing user according to the abnormal power consumption event, and further process the electricity stealing user, and at the same time, the path optimization is carried out according to the multiple abnormal parts and the electricity stealing node, and the power transmission path of the work part is optimized, the electricity stealing node is interrupted, the electricity stealing user is effectively positioned, and the working scene corresponding to the special transformer is timely optimized online.

[0005] In order to solve the above technical problems, the present application provides an online optimization method of special transformer, which is applied to the online optimization scene of special transformer.

[0006] The online optimization method of special transformer comprises the following steps:

[0007] Positioning the working scene corresponding to the special transformer substation, and defining the corresponding working part according to the working scene corresponding to the special transformer substation;

[0008] Based on the working part, all-weather detection is carried out, and the load parameter corresponding to the working part is collected;

[0009] According to the load parameter corresponding to the working part, the corresponding load schematic diagram is matched, and the corresponding multiple abnormal parts are determined based on the load schematic diagram;

[0010] According to the multiple abnormal parts and the corresponding abnormal positions, the abnormal factors are defined, and the corresponding abnormal control logic is triggered according to the abnormal factors and the working functions of the working part;

[0011] In the abnormal control logic, the to-be-affected part is defined according to the abnormal factors and the working functions of the working part, and the abnormal power use event corresponding to the abnormal power user is defined according to the comparison between the to-be-affected part and the abnormal power user, and it is judged whether the abnormal power user is a power stealing user according to the abnormal power use event;

[0012] If the abnormal power user is a power stealing user, the power stealing path is defined based on the reverse tracing of the power stealing user, the corresponding power stealing node is defined according to the power stealing path, the path optimization is carried out according to the multiple abnormal parts and the power stealing node, and the power transmission path of the working part is optimized, and the power stealing node is interrupted.

[0013] Optionally, the positioning of the working scene corresponding to the special transformer substation, and the definition of the corresponding working part according to the working scene corresponding to the special transformer substation, comprises:

[0014] Collecting the power consumption information of the special transformer;

[0015] Defining the positioning information of the special transformer according to the power consumption information of the special transformer;

[0016] Based on the positioning information of the special transformer, the positioning detection is carried out, and the working scene corresponding to the special transformer substation is positioned;

[0017] Based on the power consumption information of the special transformer, the corresponding traversal mode is matched, the traversal of the working scene corresponding to the special transformer substation is triggered based on the traversal mode, and the corresponding working part is defined in the traversal process of the working scene corresponding to the special transformer substation.

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

[0019] Freezing the working part;

[0020] Based on the working part, multiple detection nodes are constructed, and all-weather detection is carried out in the multiple detection nodes;

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

[0022] Define load integration mode according to multiple sub-load parameters and corresponding positions;

[0023] Correlate multiple sub-load parameters, functions corresponding to work parts, and load integration mode;

[0024] Define load parameters corresponding to work parts according to multiple sub-load parameters, functions corresponding to work parts, and load integration mode.

[0025] Optionally, matching corresponding load schematic diagram according to load parameters corresponding to work parts, determining corresponding multiple abnormal parts based on load schematic diagram, includes:

[0026] Fixing load parameters corresponding to work parts;

[0027] Collecting multiple load parameters, and matching corresponding load schematic diagram according to multiple load parameters and corresponding work time points;

[0028] Traversing load schematic diagram, and dividing multiple load areas according to load schematic diagram;

[0029] Defining abnormal intervals according to area identification of multiple load areas;

[0030] Correlating multiple abnormal intervals, determining corresponding multiple abnormal parts according to multiple abnormal intervals, load schematic diagram positioning, and each work part.

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

[0032] Fixing multiple abnormal parts, and defining abnormal positions corresponding to multiple abnormal parts;

[0033] Defining abnormal factors based on multiple abnormal parts and corresponding abnormal positions;

[0034] Correlating abnormal factors and work functions of work parts;

[0035] Triggering corresponding abnormal control logic according to abnormal factors and work functions of work parts, at this time, defining corresponding abnormal coefficients based on abnormal factors and work functions of work parts, and defining corresponding abnormal control logic according to abnormal coefficients and abnormal control table.

[0036] Optionally, in the abnormality management logic, the to-be-affected part is defined according to the abnormality factor and the work function of the work part, and the abnormality event corresponding to the abnormality user is defined according to the comparison between the to-be-affected part and the abnormality user, and whether the abnormality user is a power stealing user is determined according to the abnormality event, and the abnormality management logic further comprises:

[0037] In the abnormality management logic, the to-be-affected part is defined according to the abnormality factor and the work function of the work part;

[0038] The to-be-affected part is located, and the corresponding to-be-affected time is defined according to the reverse tracing of the to-be-affected part;

[0039] The plurality of power users associated with the special transformer are located, and the plurality of power users and the to-be-affected time are associated.

[0040] Optionally, in the abnormality management logic, the to-be-affected part is defined according to the abnormality factor and the work function of the work part, and the abnormality event corresponding to the abnormality user is defined according to the comparison between the to-be-affected part and the abnormality user, and whether the abnormality user is a power stealing user is determined according to the abnormality event, and the abnormality management logic further comprises:

[0041] The power consumption parameters of the plurality of power users at the to-be-affected time are collected in real time;

[0042] The corresponding power consumption schematic diagram is constructed according to the power consumption parameters of the plurality of power users at the to-be-affected time, and the abnormality user is defined based on the plurality of power users and the corresponding power consumption schematic diagram;

[0043] The abnormality event corresponding to the abnormality user is defined according to the comparison between the to-be-affected part and the abnormality user;

[0044] Whether the abnormality user is a power stealing user is determined according to the abnormality event.

[0045] Optionally, if the abnormality user is a power stealing user, the power stealing path is defined based on the reverse tracing of the power stealing user, the corresponding power stealing node is defined according to the power stealing path, the path is optimized according to the plurality of abnormal parts and the power stealing node, the power transmission path of the work part is optimized, and the power stealing node is interrupted, and the abnormality management logic further comprises:

[0046] The abnormality event is located, and the over-consumption type is defined according to the identification of the abnormality event;

[0047] The power stealing user is defined based on the over-consumption type, the power consumption operation scene of the abnormality user, and the past power consumption bill of the abnormality user.

[0048] Optionally, if the abnormal electricity user is a power stealing user, a power stealing path is defined based on reverse tracing of the power stealing user, corresponding power stealing nodes are defined according to the power stealing path, path optimization is performed according to the multiple abnormal parts and the power stealing nodes, and the power transmission path of the working part is optimized according to the electricity path of the abnormal electricity user and the optimized path; meanwhile, the power stealing nodes are interrupted, and the method further comprises:

[0049] If the abnormal electricity user is a power stealing user, a power stealing path is defined based on reverse tracing of the power stealing user;

[0050] Corresponding power stealing nodes are defined according to the power stealing path and the electricity path of the abnormal electricity user;

[0051] Path optimization is performed according to the multiple abnormal parts and the power stealing nodes;

[0052] An optimized path is output based on the multiple abnormal parts and the power stealing nodes;

[0053] The power transmission path of the working part is optimized according to the optimized path and the electricity path of the abnormal electricity user; meanwhile, the power stealing nodes are located and interrupted.

[0054] In addition, the embodiment of the application also provides an online optimization method and system of special transformer, which comprises:

[0055] A working module is configured to locate a working scenario corresponding to the special transformer and define a working part corresponding to the working scenario of the special transformer;

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

[0057] An abnormality module is configured to match a corresponding load schematic diagram according to the load parameters corresponding to the working part, determine multiple abnormal parts based on the load schematic diagram;

[0058] An abnormality control module is configured to define abnormal factors according to the multiple abnormal parts and corresponding abnormal positions, and trigger corresponding abnormality control logic according to the abnormal factors and working functions of the working part;

[0059] A judgment module is configured to define an affected part according to the abnormal factors and working functions of the working part in the abnormality control logic, define an abnormal electricity event corresponding to an abnormal electricity user according to the affected part and the abnormal electricity user, and judge whether the abnormal electricity user is a power stealing user according to the abnormal electricity event;

[0060] The path optimization module is used for defining a power stealing path based on reverse tracing of the power stealing user if the abnormal power user is a power stealing user, defining corresponding power stealing nodes according to the power stealing path, performing path optimization according to the multiple abnormal parts and the power stealing nodes, optimizing the power transmission path of the working part, and interrupting the power stealing nodes.

[0061] In the embodiment of the present application, the working scene corresponding to the special transformer substation is located by the method in the embodiment of the present application, and the corresponding working part is defined according to the working scene corresponding to the special transformer substation; the working part is detected all day long, 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 multiple abnormal parts are determined based on the load schematic diagram, so as to be clear to the multiple abnormal parts, so as to control in multiple dimensions according to the load schematic diagram, and fully consider the matching of the load parameters corresponding to the working part.

[0062] Further, the abnormal factor is defined according to the multiple abnormal parts and the abnormal positions, and the corresponding abnormal control logic is triggered according to the abnormal factor and the working function of the working part; in the abnormal control logic, the to-be-affected part is defined according to the abnormal factor and the working function of the working part, so as to control the to-be-affected part, and the abnormal power use event is clear, so as to determine whether the abnormal power user is a power stealing user according to the abnormal power use event, and then further targeted processing is performed on the power stealing user, and the power transmission path of the working part is optimized according to the multiple abnormal parts and the power stealing nodes, the power stealing nodes are interrupted, the power stealing user is effectively located, and the working scene corresponding to the special transformer substation is online optimized in time. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0064] Figure 1 is a flowchart of the online optimization method of the special transformer in the embodiment of the present application;

[0065] Figure 2 is a flowchart of S11 in the online optimization method of the special transformer in the embodiment of the present application;

[0066] Figure 3 is a flowchart of S12 in the online optimization method of the special transformer in the embodiment of the present application;

[0067] Figure 4 is a flowchart of S13 in the online optimization method for special transformer voltage in the embodiments of the present application;

[0068] Figure 5 is a flowchart of S14 in the online optimization method for special transformer voltage in the embodiments of the present application;

[0069] Figure 6 is a flowchart of S15 in the online optimization method for special transformer voltage in the embodiments of the present application;

[0070] Figure 7 is a flowchart of S16 in the online optimization method for special transformer voltage in the embodiments of the present application;

[0071] Figure 8 is a structural composition diagram of the online optimization system for special transformer voltage in the embodiments of the present application;

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

[0073] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0074] Please refer to Figures 1 to 9 , an online optimization method for special transformer voltage is applied to an online optimization scenario for special transformer voltage. The online optimization method for special transformer voltage comprises:

[0075] Step S11: locating a working scenario corresponding to the special transformer voltage, and defining a corresponding working part according to the working scenario corresponding to the special transformer voltage;

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

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

[0078] Step S14: defining an abnormal factor according to the plurality of abnormal parts and the corresponding abnormal positions, and triggering a corresponding abnormal control logic according to the abnormal factor and the working function of the working part;

[0079] Step S15: In the abnormal management logic, the affected part is defined according to the abnormal factor and the work function of the work part, and the abnormal power use event corresponding to the abnormal power use user is defined according to the affected part and the comparison of the abnormal power use user, and whether the abnormal power use user is a power stealing user is judged according to the abnormal power use event;

[0080] Step S16: If the abnormal power use user is a power stealing user, the power stealing path is defined based on the reverse tracing of the power stealing user, the corresponding power stealing node is defined according to the power stealing path, the path optimization is performed according to the multiple abnormal parts and the power stealing node, the power transmission path of the work part is optimized, and the power stealing node is interrupted.

[0081] In the embodiment of the application, through the method in the embodiment of the application, the work scene corresponding to the special transformer substation is located, and the corresponding work part is defined according to the work scene corresponding to the special transformer substation; all-weather detection is performed based on the work part, and the load parameter corresponding to the work part is collected; the corresponding load schematic diagram is matched according to the load parameter corresponding to the work part, and the multiple abnormal parts are determined based on the load schematic diagram, so that the multiple abnormal parts are determined, so that the multiple dimensions are controlled according to the load schematic diagram, and the matching of the load parameter corresponding to the work part is fully considered.

[0082] Further, the abnormal factor is defined according to the multiple abnormal parts and the corresponding abnormal position, and the corresponding abnormal management logic is triggered according to the abnormal factor and the work function of the work part; in the abnormal management logic, the affected part is defined according to the abnormal factor and the work function of the work part, so as to perform targeted management according to the affected part, and the abnormal power use event is determined, so as to judge whether the abnormal power use user is a power stealing user according to the abnormal power use event, and then further targeted processing is performed on the power stealing user, and the power transmission path of the work part is optimized according to the multiple abnormal parts and the power stealing node, and the power stealing node is interrupted, so as to effectively locate the power stealing user and timely optimize the work scene corresponding to the special transformer substation online.

[0083] Reference Figure 2 In step S11, the work scene corresponding to the special transformer substation is located, and the corresponding work part is defined according to the work scene corresponding to the special transformer substation;

[0084] In the specific implementation process of the application, the specific steps can be:

[0085] S111: Collecting power use information of the special transformer;

[0086] S112: Defining positioning information of the special transformer according to the power use information of the special transformer;

[0087] S113: positioning detection is performed based on the positioning information of the special transformer, and the working scene corresponding to the special transformer is positioned;

[0088] S114: the corresponding traversal mode is matched based on the power utilization information of the special transformer, the traversal of the working scene corresponding to the special transformer is triggered based on the traversal mode, and the corresponding working part is defined in the traversal process of the working scene corresponding to the special transformer.

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

[0090] At this time, positioning detection is performed based on the positioning information of the special transformer, and the working scene corresponding to the special transformer is positioned, so as to fix the working scene corresponding to the special transformer in the positioning detection of the special transformer, introduce the working scene corresponding to the special transformer, and thereby match the corresponding traversal mode based on the power utilization information of the special transformer, trigger the traversal of the working scene corresponding to the special transformer based on the traversal mode, and define the corresponding working part in the traversal process of the working scene corresponding to the special transformer, so as to perform targeted traversal based on the traversal mode, and thereby control the corresponding working traversal in the traversal process. Optionally, the working scene corresponding to the special transformer is the scene where the special transformer is in the working state, and involves components such as the power supply room and the current transmission line of the special transformer. The traversal mode includes overall traversal or local traversal.

[0091] Reference Figure 3 In step S12, all-weather detection is performed based on the working part, and the load parameter corresponding to the working part is collected;

[0092] In the specific implementation process of the present application, the specific steps can be:

[0093] S121: fix the working part;

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

[0095] S123: define the sub-load parameter of each detection node based on the all-weather detection of the plurality of detection nodes;

[0096] S124: define the load integration mode according to the plurality of sub-load parameters and the corresponding positions;

[0097] S125: associate the plurality of sub-load parameters, the function corresponding to the working part, and the load integration mode;

[0098] S126: define the load parameter corresponding to the working part according to the plurality of sub-load parameters, the function corresponding to the working part, and the load integration mode.

[0099] In the embodiment of the present application, the working part is fixed, and the working part is further controlled, at this time, a plurality of detection nodes are constructed based on the working part, and all-weather detection is performed in the plurality of detection nodes, so as to control the plurality of detection nodes in real time, so as to define the sub-load parameter of each detection node based on the all-weather detection of the plurality of detection nodes, and the sub-load parameter of each detection node is introduced, and the accuracy of the sub-load parameter of each detection node is ensured. Optionally, the working part is a working component in the working scene corresponding to the special transformer, which can be a power supply, a circuit conveying component, etc. The detection node is a node that needs to be detected in the working part, which can be a position through which the current in the working part passes. The sub-load parameter is a part of the load parameter, which is a current parameter, a voltage parameter, etc. corresponding to the detection node.

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

[0101] Therefore, the plurality of sub-load parameters, the function corresponding to the working part, and the load integration mode are associated; the load parameter corresponding to the working part is defined according to the plurality of sub-load parameters, the function corresponding to the working part, and the load integration mode, and the load parameter corresponding to the working part is controlled, so as to ensure the accuracy of the load parameter corresponding to the working part. Optionally, the load parameter is a whole current parameter or a whole voltage parameter of the working part.

[0102] Reference Figure 4 In step S13, the corresponding load schematic diagram is matched according to the load parameter corresponding to the working part, and the plurality of abnormal parts corresponding to the load schematic diagram are determined based on the load schematic diagram.

[0103] In the specific implementation process of the present application, the specific steps can be:

[0104] S131: fix the load parameter corresponding to the working part;

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

[0106] S133: Traverse the load schematic diagram, and divide multiple load regions according to the load schematic diagram;

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

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

[0109] In the embodiment of the application, the working scene corresponding to the special transformer substation is located, and the corresponding working part is defined according to the working scene corresponding to the special transformer substation; all-weather detection is carried out 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 that the multiple abnormal parts are determined, so that the multiple dimensions are controlled according to the load schematic diagram, and the matching of the load parameters corresponding to the working part is fully considered.

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

[0111] Further, the load schematic diagram is traversed, and multiple load regions are divided according to the load schematic diagram; the abnormal interval is defined according to the region identification of multiple load regions, so that the abnormal interval is introduced, multiple abnormal intervals are associated, and corresponding multiple abnormal parts are determined according to multiple abnormal intervals, load schematic diagram positioning, and each working part, so that the multiple abnormal parts are determined, and the overall control of the multiple abnormal parts is realized. Optionally, the load schematic diagram is constructed by load parameters and corresponding working time points, the vertical coordinate is the load parameter, and the horizontal coordinate is the corresponding working time point; the load region is part of the load schematic diagram and is segmented from the load schematic diagram, the load region corresponds to the corresponding working part, and the abnormal interval is an interval of abnormal load parameters.

[0112] Reference Figure 5 S14: Define an abnormal factor according to multiple abnormal parts and corresponding abnormal positions, and trigger corresponding abnormal control logic according to the abnormal factor and the working function of the working part;

[0113] In the specific implementation process of the application, the specific steps can be:

[0114] S141: multiple abnormal parts are determined, and abnormal positions corresponding to the multiple abnormal parts are defined;

[0115] S142: an abnormal factor is defined based on the multiple abnormal parts and the corresponding abnormal positions;

[0116] S143: the abnormal factor is associated with the work function of the work part;

[0117] S144: the corresponding abnormal control logic is triggered according to the abnormal factor and the work function of the work part, at this time, the corresponding abnormal coefficient is defined based on the abnormal factor and the work function of the work part, and the corresponding abnormal control logic is defined according to the abnormal coefficient and the abnormal control table.

[0118] In the embodiment of the application, multiple abnormal parts are determined, and abnormal positions corresponding to the multiple abnormal parts are defined, so that multiple abnormal parts and corresponding positions are introduced, thereby realizing multi-dimensional control of the abnormal factor based on the multiple abnormal parts and the corresponding abnormal positions, and ensuring the accuracy of the abnormal factor. Optionally, the abnormal factor includes current abnormality, voltage abnormality, component abnormality, etc., which are not limited here.

[0119] At this time, the abnormal factor is associated with the work function of the work part, and multi-dimensional control is performed on the abnormal factor and the work function of the work part, so as to trigger the corresponding abnormal control logic according to the abnormal factor and the work function of the work part, thereby performing abnormal control based on the abnormal control logic, at this time, the corresponding abnormal coefficient is defined based on the abnormal factor and the work function of the work part, and the corresponding abnormal control logic is defined according to the abnormal coefficient and the abnormal control table.

[0120] Reference Figure 6 , S15: in the abnormal control logic, the affected part is defined according to the abnormal factor and the work function of the work part, and the abnormal power consumption event corresponding to the abnormal power consumption user is defined according to the comparison between the affected part and the abnormal power consumption user, and it is judged whether the abnormal power consumption user is a power stealing user according to the abnormal power consumption event;

[0121] In the specific implementation process of the application, the specific steps can be:

[0122] S151: in the abnormal control logic, the affected part is defined according to the abnormal factor and the work function of the work part;

[0123] S152: the affected part is determined, and the corresponding affected time is defined according to the reverse tracing of the affected part;

[0124] S153: multiple power consumption users associated with the special transformer are located, and the multiple power consumption users are associated with the affected time;

[0125] S154: collecting power consumption parameters of the plurality of power consumption users at the to-be-affected time in real time; constructing a corresponding power consumption sketch map according to the power consumption parameters of the plurality of power consumption users at the to-be-affected time, and defining an abnormal power consumption user based on the plurality of power consumption users and the corresponding power consumption sketch map;

[0126] S155: defining an abnormal power consumption event corresponding to the abnormal power consumption user according to a comparison between the to-be-affected part and the abnormal power consumption user;

[0127] S156: judging whether the abnormal power consumption user is a power stealing user according to the abnormal power consumption event.

[0128] In the embodiment of the present application, in the abnormal control logic, the to-be-affected part is defined according to the abnormal factor and the work function of the work part, so as to control in multiple dimensions through the abnormal factor and the work function of the work part, so as to ensure the accuracy of the to-be-affected part.

[0129] At this time, the to-be-affected part is fixed, and the corresponding to-be-affected time is defined according to the reverse tracing of the to-be-affected part, so as to clearly define the to-be-affected time, so as to introduce the to-be-affected time, and then control the to-be-affected time. Optionally, the to-be-affected part is a part that may exist an impact. The to-be-affected time is the occurrence time corresponding to the to-be-affected part.

[0130] Therefore, the plurality of power consumption users associated with the special transformer are located, the plurality of power consumption users and the to-be-affected time are associated, the power consumption parameters of the plurality of power consumption users at the to-be-affected time are collected in real time, the corresponding power consumption sketch map is constructed according to the power consumption parameters of the plurality of power consumption users at the to-be-affected time, and the abnormal power consumption user is defined based on the plurality of power consumption users and the corresponding power consumption sketch map, so as to control the whole through the plurality of power consumption users and the corresponding power consumption sketch map, so as to fix the abnormal power consumption user, and realize the identification of the abnormal power consumption user.

[0131] Further, the abnormal power consumption event corresponding to the abnormal power consumption user is defined according to the comparison between the to-be-affected part and the abnormal power consumption user, and whether the abnormal power consumption user is a power stealing user is judged according to the abnormal power consumption event, so as to realize the judgment of the power stealing user. Optionally, the power stealing user is a user who steals power. The abnormal power consumption event is an event that exists abnormal power consumption, which can be a power stealing event, a high load event, which is not limited here.

[0132] Reference Figure 7 , S16: if the abnormal power consumption user is a power stealing user, defining a power stealing path based on the reverse tracing of the power stealing user, defining a corresponding power stealing node according to the power stealing path, performing path optimization according to the plurality of abnormal parts and the power stealing node, and optimizing the power transmission path of the work part, at the same time, interrupting the power stealing node;

[0133] In the implementation of the present application, the specific steps can be:

[0134] S161: defining an abnormal electricity use event, and defining an excessive electricity use type according to the identification of the abnormal electricity use event;

[0135] S162: defining a power stealing user based on the excessive electricity use type, the electricity use operation scene of the abnormal electricity user, and the past electricity bills of the abnormal electricity user;

[0136] S163: if the abnormal electricity user is a power stealing user, defining a power stealing path based on the reverse tracing of the power stealing user;

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

[0138] S165: performing path optimization according to the multiple abnormal parts and the power stealing node;

[0139] S166: outputting an optimized path based on the multiple abnormal parts and the power stealing node;

[0140] S167: optimizing the power transmission path of the working part according to the optimized path and the electricity use path of the abnormal electricity user; at the same time, locating the power stealing node and performing interruption processing on the power stealing node.

[0141] In the implementation of the present application, the abnormal factors are defined according to the multiple abnormal parts and the corresponding abnormal positions, and the corresponding abnormal control logic is triggered according to the abnormal factors and the working functions of the working part; in the abnormal control logic, the to-be-affected part is defined for the abnormal factors and the working functions of the working part, so as to perform targeted control according to the to-be-affected part and determine the abnormal electricity use event, thereby judging whether the abnormal electricity user is a power stealing user according to the abnormal electricity use event, and further performing targeted processing on the power stealing user; at the same time, the path optimization is performed according to the multiple abnormal parts and the power stealing node, and the power transmission path of the working part is optimized, and the interruption processing is performed on the power stealing node, thereby ensuring the effective positioning of the power stealing user and the online optimization of the working scene corresponding to the special transformer substation. Optionally, the abnormal control logic is a logic for controlling the abnormal factors.

[0142] At this time, the abnormal electricity use event is defined, and the excessive electricity use type is defined according to the identification of the abnormal electricity use event, so that the excessive electricity use type is introduced, the excessive electricity use type is further controlled, and thereby the power stealing user is defined based on the excessive electricity use type, the electricity use operation scene of the abnormal electricity user, and the past electricity bills of the abnormal electricity user, and the determination of the power stealing user is realized.

[0143] Therefore, if the abnormal power user is a power stealing user, a power stealing path is defined based on reverse tracing of the power stealing user, corresponding power stealing nodes are defined according to the power stealing path and a power consumption path of the abnormal power user, path optimization is performed according to the multiple abnormal parts and the power stealing nodes, and the optimized path is output based on the multiple abnormal parts and the power stealing nodes, so that the power stealing nodes are interrupted, the power stealing user is effectively located, and the working scene corresponding to the special transformer substation is timely optimized online. In addition, the power stealing nodes are located and interrupted, the power stealing user is effectively located, and the working scene corresponding to the special transformer substation is timely optimized online. Optionally, the power stealing path is the path of the stolen power, and the optimized path refers to the optimized path.

[0144] Specifically,

[0145] The multiple sensing units are respectively installed on the overhead line, current data is obtained by induction, on-site calculation is performed, and the data is sent to the operation terminal through the micro electric module in the sensing unit. The obtained data can be displayed by accessing the operation terminal, and the data can be analyzed.

[0146] In the embodiment of the application, through the method in the embodiment of the application, the working scene corresponding to the special transformer substation is located, and the corresponding working part is defined according to the working scene corresponding to the special transformer substation. The working part is detected all day long, 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 multiple abnormal parts are determined based on the load schematic diagram, so that the multiple abnormal parts are determined, and the load schematic diagram is controlled in multiple dimensions, and the matching of the load parameters corresponding to the working part is fully considered.

[0147] Further, the abnormal factor is defined according to the multiple abnormal parts and the abnormal positions, the abnormal control logic is triggered according to the abnormal factor and the working function of the working part, the affected part is defined according to the abnormal factor and the working function of the working part in the abnormal control logic, the abnormal power consumption event is determined according to the affected part, the abnormal power consumption user is determined according to the abnormal power consumption event, and the abnormal power consumption user is further processed, the path optimization is performed according to the multiple abnormal parts and the power stealing nodes, the power transmission path of the working part is optimized, the power stealing nodes are interrupted, the power stealing user is effectively located, and the working scene corresponding to the special transformer substation is timely optimized online.

[0148] Please refer to Figure 8 , Figure 8 is a structural composition diagram of the online optimization system of the special transformer in the embodiment of the application.

[0149] AsFigure 8 As shown in the figure, a dedicated transformer online optimization system, the human- post precise bidirectional mutual matching system comprises:

[0150] The work module 21 is used for positioning the work scene corresponding to the dedicated transformer, and defining the corresponding work part according to the work scene corresponding to the dedicated transformer;

[0151] The acquisition module 22 is used for all-weather detection based on the work part, and acquires the load parameter corresponding to the work part;

[0152] The exception module 23 is used for matching the corresponding load schematic diagram according to the load parameter corresponding to the work part, and determining a plurality of abnormal parts based on the load schematic diagram;

[0153] The exception control module 24 is used for defining the abnormal factor according to the plurality of abnormal parts and the corresponding abnormal position, and triggering the corresponding exception control logic according to the abnormal factor and the work function of the work part;

[0154] The judgment module 25 is used for defining the to-be-affected part in the exception control logic for the abnormal factor and the work function of the work part, defining the abnormal power consumption event corresponding to the abnormal power consumption user according to the comparison between the to-be-affected part and the abnormal power consumption user, and judging whether the abnormal power consumption user is a power stealing user according to the abnormal power consumption event;

[0155] The path optimization module 26 is used for defining the power stealing path based on the reverse tracing of the power stealing user if the abnormal power consumption user is a power stealing user, defining the corresponding power stealing node according to the power stealing path, performing path optimization according to the plurality of abnormal parts and the power stealing node, optimizing the power transmission path of the work part, and interrupting the power stealing node.

[0156] Please refer to Figure 9 , the electronic device 40 according to the embodiment of the present application will be described below with reference to Figure 9 . Figure 9 The electronic device 40 shown is merely an example, and should not impose any limitation on the function and use range of the embodiments of the present application.

[0157] As shown in Figure 9 , the electronic device 40 is in the form of a general computing device. The components of the electronic device 40 can include but are not limited to the above-mentioned at least one processing unit 41, the above-mentioned at least one storage unit 42, and the bus 43 connecting different system components, including the storage unit 42 and the processing unit 41.

[0158] The storage unit stores program code, which can be executed by the processing unit 41 to perform the steps described in the "Embodiment Methods" section of this specification according to various exemplary embodiments of the present invention.

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

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

[0161] Bus 43 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0162] Electronic device 40 can also communicate with one or more external devices (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 40, and / or with any device that enables electronic device 40 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed through input / output (I / O) interface 44. Furthermore, electronic device 40 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 45. Figure 9 As shown, network adapter 45 communicates with other modules of electronic device 40 via bus 43. It should be understood that, although... Figure 9 As not shown, other hardware and / or software modules may be used in conjunction with 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 above description of the embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a U disk, a mobile hard disk, etc.) or on a network, and includes a plurality of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.

[0164] Those skilled in the art can understand that all or part of the steps of the various methods of the above embodiments can be completed by instructing the relevant hardware through a program. 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 magnetic disk or an optical disk, etc. The storage medium has computer program instructions stored therein, and when the computer program instructions are executed by a computer, the computer performs the method according to the above.

[0165] In addition, the above describes in detail the online optimization system and the system provided by the special transformer of the embodiments of the present application. The principles and implementation manners of the present application are described by using specific examples. The above embodiment is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range can be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A dedicated voltage variation online optimization method, characterized in that, The application is applied to an online optimization scene of a special transformer; The online optimization method of the special transformer comprises: Positioning a working scene corresponding to the special transformer, and defining a working part corresponding to the special transformer according to the working scene corresponding to the special transformer; Performing all-weather detection based on the working part, and collecting a load parameter corresponding to the working part; Matching a corresponding load schematic diagram according to the load parameter corresponding to the working part, and determining a plurality of abnormal parts based on the load schematic diagram; Defining an abnormal factor according to the plurality of abnormal parts and corresponding abnormal positions, and triggering corresponding abnormal control logic according to the abnormal factor and a working function of the working part; In the abnormal control logic, defining an affected part according to the abnormal factor and the working function of the working part, and defining an abnormal power consumption event corresponding to an abnormal power consumption user according to a comparison between the affected part and the abnormal power consumption user, and determining whether the abnormal power consumption user is a power stealing user according to the abnormal power consumption event, comprising: in the abnormal control logic, defining an affected part according to the abnormal factor and the working function of the working part; determining the affected part, and defining a corresponding affected time according to a reverse tracing of the affected part; positioning a plurality of power consumption users associated with the special transformer, associating the plurality of power consumption users and the affected time; collecting power consumption parameters of the plurality of power consumption users at the affected time in real time; constructing a corresponding power consumption schematic diagram according to the power consumption parameters of the plurality of power consumption users at the affected time, and defining an abnormal power consumption user based on the plurality of power consumption users and the corresponding power consumption schematic diagram; defining an abnormal power consumption event corresponding to the abnormal power consumption user according to a comparison between the affected part and the abnormal power consumption user; determining whether the abnormal power consumption user is a power stealing user according to the abnormal power consumption event; If the abnormal power consumption user is a power stealing user, defining a power stealing path based on a reverse tracing of the power stealing user, defining a corresponding power stealing node according to the power stealing path, performing path optimization according to the plurality of abnormal parts and the power stealing node, and optimizing a power transmission path of the working part, and simultaneously, interrupting the power stealing node.

2. The dedicated variable pressure on-line optimization method of claim 1, wherein, The positioning of the working scene corresponding to the special transformer, and the definition of the working part corresponding to the special transformer according to the working scene corresponding to the special transformer, comprises: Collecting power consumption information of the special transformer; Defining positioning information of the special transformer according to the power consumption information of the special transformer; Performing positioning detection based on the positioning information of the special transformer, and positioning the working scene corresponding to the special transformer; Matching a corresponding traversal mode based on the power consumption information of the special transformer, triggering traversal of the working scene corresponding to the special transformer based on the traversal mode, and defining the working part in the traversal process of the working scene corresponding to the special transformer.

3. The dedicated voltage on-line optimization method of claim 2, wherein, The all-weather detection based on the working part, and the collection of the load parameter corresponding to the working part, comprises: Determining the working part; Constructing a plurality of detection nodes based on the working part, and performing all-weather detection in the plurality of detection nodes; Defining a sub-load parameter of each detection node based on the all-weather detection of the plurality of detection nodes; Defining a load integration mode according to the plurality of sub-load parameters and corresponding positions; Associating the plurality of sub-load parameters, a function corresponding to the working part, and the load integration mode; According to the multiple sub-load parameters, the functions corresponding to the working parts, and the load integration mode, the load parameters corresponding to the working parts are defined.

4. The dedicated voltage-converted online optimization method of claim 3, wherein, The load parameters corresponding to the working parts are matched with the corresponding load schematic diagram based on the load parameters corresponding to the working parts. The load parameters corresponding to the working parts are defined. 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. The load schematic diagram is traversed, and multiple load regions are divided according to the load schematic diagram. The abnormal interval is defined according to the region identification of the multiple load regions. The multiple abnormal parts are determined according to the multiple abnormal intervals, the load schematic diagram positioning, and the working parts.

5. The dedicated voltage on-line optimization method of claim 4, wherein, The abnormal factors are defined according to the multiple abnormal parts and the corresponding abnormal positions, and the corresponding abnormal control logic is triggered according to the abnormal factors and the working functions of the working parts. The multiple abnormal parts are defined, and the abnormal positions corresponding to the multiple abnormal parts are defined. The abnormal factors are defined based on the multiple abnormal parts and the corresponding abnormal positions. The abnormal factors are associated with the working functions of the working parts. The corresponding abnormal control logic is triggered according to the abnormal factors and the working functions of the working parts, at which time the corresponding abnormal coefficient is defined based on the abnormal factors and the working functions of the working parts, and the corresponding abnormal control logic is defined according to the abnormal coefficient and the abnormal control table.

6. The dedicated variable pressure on-line optimization method of claim 1, wherein, If the abnormal electricity user is a power stealing user, the power stealing path is defined based on the reverse tracing of the power stealing user, the corresponding power stealing node is defined according to the power stealing path, the path optimization is performed according to the multiple abnormal parts and the power stealing node, and the power transmission path of the working part is optimized, and the power stealing node is interrupted. The abnormal electricity event is defined, and the excessive electricity type is defined according to the identification of the abnormal electricity event. The power stealing user is defined based on the excessive electricity type, the electricity operation scene of the abnormal electricity user, and the past electricity bill of the abnormal electricity user.

7. The dedicated variable pressure on-line optimization method of claim 6, wherein, If the abnormal electricity user is a power stealing user, the power stealing path is defined based on the reverse tracing of the power stealing user, the corresponding power stealing node is defined according to the power stealing path, the path optimization is performed according to the multiple abnormal parts and the power stealing node, and the power transmission path of the working part is optimized, and the power stealing node is interrupted. If the abnormal electricity user is a power stealing user, the power stealing path is defined based on the reverse tracing of the power stealing user. The corresponding power stealing node is defined according to the power stealing path and the electricity path of the abnormal electricity user. The path optimization is performed according to the multiple abnormal parts and the power stealing node. The optimized path is output based on the multiple abnormal parts and the power stealing node. The power transmission path of the working part is optimized according to the optimized path and the electricity path of the abnormal electricity user, and the power stealing node is located and interrupted.

8. An online optimization system for dedicated voltage variations, characterized in that, The online optimization system of the special transformer is applied to the online optimization method of the special transformer as claimed in any one of claims 1-7, and the online optimization system of the special transformer comprises: The working module is used for positioning a working scene corresponding to the special transformer substation and defining a corresponding working part according to the working scene corresponding to the special transformer substation. The acquisition module is used for all-weather detection based on the working part and acquisition of a load parameter corresponding to the working part. The exception module is used for matching a corresponding load schematic diagram according to the load parameter corresponding to the working part, determining a plurality of abnormal parts based on the load schematic diagram. The exception control module is used for defining an exception factor according to the plurality of abnormal parts and a corresponding abnormal position and triggering a corresponding exception control logic according to the exception factor and a working function of the working part. The judgment module is used for defining an affected part according to the exception factor and the working function of the working part in the exception control logic, defining an abnormal power consumption event corresponding to an abnormal power consumption user according to a comparison between the affected part and the abnormal power consumption user, and judging whether the abnormal power consumption user is a power stealing user according to the abnormal power consumption event, including defining the affected part according to the exception factor and the working function of the working part in the exception control logic, defining a corresponding affected time according to a reverse tracking of the affected part, positioning a plurality of power consumption users associated with the special transformer, associating the plurality of power consumption users and the affected time, acquiring power consumption parameters of the plurality of power consumption users at the affected time in real time, constructing a corresponding power consumption schematic diagram according to the power consumption parameters of the plurality of power consumption users at the affected time, defining the abnormal power consumption user based on the plurality of power consumption users and the corresponding power consumption schematic diagram, defining the abnormal power consumption event corresponding to the abnormal power consumption user according to a comparison between the affected part and the abnormal power consumption user, and judging whether the abnormal power consumption user is the power stealing user according to the abnormal power consumption event. The path optimization module is used for defining a power stealing path based on a reverse tracking of the power stealing user if the abnormal power consumption user is the power stealing user, defining a corresponding power stealing node according to the power stealing path, performing path optimization according to the plurality of abnormal parts and the power stealing node, optimizing a power transmission path of the working part, and interrupting the power stealing node at the same time.

Images