Transformer three-phase imbalance treatment method and system based on big data

Abstract

The invention relates to the technical field of power distribution networks, in particular to a transformer three-phase imbalance treatment method and system based on big data. Firstly, three-phase power values of power distribution network users are collected through an intelligent electric meter, a power mean value is determined through the three-phase power values, and N-phase power of a power distribution network is calculated based on the three-phase power values of the power distribution network users and the power mean value; and then calculating the three-phase unbalance degree of the power distribution network based on the three-phase voltage value of the power distribution network user, judging whether a three-phase system needs load switching based on the three-phase unbalance degree, and then formulating a control adjustment strategy of load switching according to the size and relation of the three-phase active power. Based on the adjustment strategy, selecting a phase-change switch to carry out phase-change switching of the load, so that partial load or load combination in the heavy-load phase is switched to a light-load item; when the method is used for monitoring, evaluating and controlling the distribution transformer district based on a certain frequency, the dynamic unbalance degree of a three-phase system can be greatly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution networks, and in particular to a method and system for controlling three-phase imbalance of a transformer based on big data. Background Art

[0002] Low-voltage distribution networks have been a key area of ​​national investment in recent years, primarily aimed at enhancing operational reliability, improving energy utilization, and strengthening user engagement. Three-phase imbalance in distribution networks is a common power quality issue across nearly all distribution areas. Three-phase imbalance refers to the inconsistency of the three-phase current or voltage amplitudes in a three-phase power system, with the amplitude difference exceeding the specified range.

[0003] Three-phase imbalance can increase transformer copper or iron losses, increasing transformer losses, affecting operating temperatures, and shortening transformer life. Low-voltage power grids mostly use a three-phase, four-wire system. Due to the unbalanced single-phase loads and the uneven timing of power consumption, three-phase imbalance in distribution transformers in low-voltage distribution networks is a more prominent problem. Existing solutions for managing three-phase imbalance need to be improved. Summary of the Invention

[0004] The main purpose of the present invention is to provide a method and system for transformer three-phase imbalance control based on big data, aiming to solve the problem that the efficiency of existing three-phase imbalance control solutions needs to be improved.

[0005] The technical solution proposed by the present invention is:

[0006] A method for managing transformer three-phase imbalance based on big data is applied to a transformer three-phase imbalance management system based on big data; the system includes a smart meter, a server, and a management module (disposed on the transformer); the smart meter and the management module are both communicatively connected to the server; the method includes:

[0007] The smart meter collects three-phase power values ​​of users in the distribution network and sends them to the server;

[0008] The server determines the power mean value P based on the three-phase power value of the distribution network user AV , and based on the three-phase power value and power mean P of the distribution network users AV Calculate the N-phase power P of the distribution network N ;

[0009] The server is based on the N-phase power P of the power distribution network N Determine whether the distribution network meets the three-phase power adjustment conditions;

[0010] If the three-phase power adjustment conditions are met, the server collects the three-phase voltage values ​​of the distribution network users in real time through the smart meter, and calculates the three-phase imbalance Y of the distribution network based on the three-phase voltage values ​​of the distribution network users. Nb ;

[0011] The server calculates the three-phase imbalance Y of the power distribution network Nb Determine whether the distribution network needs phase switching management;

[0012] If phase switching is required, the server determines the phase that needs load switching and marks it as the target phase, as well as the phase switching capacity required for switching and marks it as the target capacity;

[0013] The server controls the startup of the management module to select a phase-changing switch whose access phase corresponds to the target phase and whose access load is adapted to the target capacity, thereby performing load switching.

[0014] Preferably, the server determines the power mean value P based on the three-phase power value of the distribution network user. AV , and based on the three-phase power value and power mean P of the distribution network users AV Calculate the N-phase power P of the distribution network N ,include:

[0015] The server averages the three-phase power values ​​of the distribution network users to obtain a power mean value P AV ;

[0016] The server compares the three-phase power values ​​of the distribution network users with the power mean P AV Subtract to get the phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 ;

[0017] The server is based on the phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 Calculate the N-phase power P of the distribution network N .

[0018] Preferably, the server is based on the phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 Calculate the N-phase power P of the distribution network N The calculation formula is:

[0019]

[0020] Where, P Nis the N-phase power of the distribution network.

[0021] Preferably, the server is based on the N-phase power P of the power distribution network. N Determine whether the distribution network meets the three-phase power adjustment conditions, including:

[0022] The server will determine the N-phase power P of the power distribution network N Is it greater than the preset power limit value P? NX ;

[0023] If so, the server determines that the power distribution network meets the three-phase power adjustment conditions, controls the transformer of the power distribution network to shut down, and resets the three-phase power value.

[0024] Preferably, the three-phase voltage value includes the A-phase voltage value, the B-phase voltage value and the C-phase voltage value; if the three-phase power adjustment condition is met, the server collects the three-phase voltage value of the distribution network user in real time through the smart meter, and calculates the three-phase imbalance Y of the distribution network based on the three-phase voltage value of the distribution network user. Nb ,include:

[0025] The server obtains the maximum value U among the voltage values ​​of phase A, phase B and phase C. MAX ;

[0026] The server averages the voltage values ​​of phase A, phase B, and phase C to obtain the average voltage value of the three-phase voltage U A ;

[0027] The server is based on the maximum value U among the A phase voltage value, the B phase voltage value and the C phase voltage value. MAX , and the three-phase voltage average value U A Calculate the three-phase imbalance Y of the distribution network Nb :

[0028]

[0029] Where Y Nb is the three-phase imbalance of the distribution network.

[0030] Preferably, the server calculates the three-phase imbalance Y of the distribution network based on the Nb Determine whether the distribution network needs phase switching management, including:

[0031] The server calculates the three-phase imbalance Y of the distribution network Nb and the preset three-phase unbalance threshold Y NY Make comparisons;

[0032] When Y Nb Greater than Y NYWhen the power distribution network is in a state of emergency, the server determines that phase switching management is required.

[0033] Preferably, if phase switching management is required, the server determines the phase that requires load switching and marks it as the target phase, and the phase switching capacity required for switching and marks it as the target capacity, including:

[0034] The server determines the A-phase active power P of the distribution network user based on the three-phase power value of the distribution network user. A , B phase active power P B and C phase active power P C ;

[0035] The server is based on the active power P of phase A A , B phase active power P B , C phase active power P C , Phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P B1 Determine the phases that need load switching and the commutation capacity required for switching.

[0036] Preferably, the server is based on the active power P of phase A A , B phase active power P B , C phase active power P C , Phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P B1 Determine the phases that require load switching and the commutation capacity required for switching, including:

[0037] If P A >P B >P C The server determines that phase A and phase C are the phases that need load switching. The switching process is to select part of the single-phase load from phase A and switch it to phase C. The adjustment amount is

[0038] If P A =P B >P C The server determines that phase A and phase B are the phases that need load switching. The switching process is to select part of the single-phase load from phase B and switch it to phase C. The adjustment amount is

[0039] If P A >P B =P CThe server determines that phase B and phase C are the phases that need load switching. The switching process is to select part of the single-phase load from phase A and switch it to phase B or phase C. The adjustment amount is

[0040] Preferably, the server controls the startup of the management module to select a phase-changing switch whose access phase corresponds to the target phase and whose access load is adapted to the target capacity, thereby performing load switching, including:

[0041] The management module controls the initial numbering of each phase-changing switch to be numbered from large to small according to the current allowed phase-changing interval of each phase-changing switch;

[0042] The management module controls the dynamic change time point of each phase-changing switch after each phase-changing switching. When changing, the phase-changing switch that participated in the phase-changing switching for the last time is numbered after other switches;

[0043] The management module controls the dynamic change time point of each phase-changing switch after each phase-changing switching. The initial number of each phase-changing switch and the change number after each phase-changing switching are both numbered from large to small according to the current allowed phase-changing interval time of each phase-changing switch.

[0044] The present invention also proposes a transformer three-phase imbalance management system based on big data, which applies a transformer three-phase imbalance management method based on big data; the system includes a smart meter, a server and a management module: the smart meter and the management module are both communicatively connected to the server.

[0045] The above technical solution can achieve the following beneficial effects:

[0046] The big data-based transformer three-phase imbalance control method proposed in the present invention can improve the efficiency of three-phase imbalance control. First, the three-phase power values ​​of distribution network users are collected through smart meters, and the power average is determined based on the three-phase power values. The N-phase power of the distribution network is calculated based on the three-phase power values ​​of the distribution network users and the power average. Then, the three-phase imbalance of the distribution network is calculated based on the three-phase voltage values ​​of the distribution network users. Based on the three-phase imbalance, it is judged whether the three-phase system needs load switching. Then, according to the size and relationship of the three-phase active power, a control adjustment strategy for load switching is formulated. Based on this adjustment strategy, a phase-changing switch is selected to perform phase switching of the load, so that part of the load or load combination in the heavy-load phase is switched to the light-load item. When the method of the present invention is used to monitor, evaluate and control the distribution transformer area based on a certain frequency, the dynamic imbalance of the three-phase system can be greatly reduced, and the power supply voltage quality of the distribution station area can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 the structures shown in these drawings without paying any creative work.

[0048] Figure 1 This is a flowchart of the first embodiment of a method for controlling three-phase imbalance of a transformer based on big data proposed by the present invention. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0050] The present invention proposes a method and system for controlling three-phase imbalance of a transformer based on big data.

[0051] As attached Figure 1 As shown, in a first embodiment of a transformer three-phase unbalance management method based on big data proposed by the present invention, the method is applied to a transformer three-phase unbalance management system based on big data; the system includes a smart meter, a server, and a management module: the smart meter and the management module are both communicatively connected to the server; this embodiment includes the following steps:

[0052] Step S110: The smart meter collects three-phase power values ​​of users in the distribution network and sends them to the server.

[0053] Specifically, the three-phase power values ​​collected by the smart meter are first preprocessed to unify the units and precision of the collected data to facilitate subsequent calculations.

[0054] Step S120: The server determines the power mean value P based on the three-phase power values ​​of the distribution network users. AV , and based on the three-phase power value and power mean P of the distribution network users AV Calculate the N-phase power P of the distribution network N .

[0055] Step S130: The server is based on the N-phase power P of the power distribution network. N Determine whether the distribution network meets the three-phase power adjustment conditions.

[0056] Step S140: If the three-phase power adjustment conditions are met, the server collects the three-phase voltage values ​​of the distribution network users in real time through the smart meter, and calculates the three-phase imbalance Y of the distribution network based on the three-phase voltage values ​​of the distribution network users. Nb .

[0057] Step S150: The server calculates the three-phase imbalance Y of the power distribution network based on the calculation Nb Determine whether the distribution network needs phase-changing and switching management.

[0058] Step S160: If phase switching management is required, the server determines the phase that requires load switching and marks it as the target phase, as well as the phase switching capacity required for switching, and marks it as the target capacity.

[0059] Step S170: The server controls the governance module to start up, so as to select a phase-changing switch whose access phase corresponds to the target phase and whose access load is adapted to the target capacity, thereby performing load switching to balance the three-phase active power.

[0060] The big data-based transformer three-phase imbalance control method proposed in the present invention can improve the efficiency of three-phase imbalance control. First, the three-phase power values ​​of distribution network users are collected through smart meters, and the power average is determined based on the three-phase power values. The N-phase power of the distribution network is calculated based on the three-phase power values ​​of the distribution network users and the power average. Then, the three-phase imbalance of the distribution network is calculated based on the three-phase voltage values ​​of the distribution network users. Based on the three-phase imbalance, it is judged whether the three-phase system needs load switching. Then, according to the size and relationship of the three-phase active power, a control adjustment strategy for load switching is formulated. Based on this adjustment strategy, a phase-changing switch is selected to perform phase switching of the load, so that part of the load or load combination in the heavy-load phase is switched to the light-load item. When the method of the present invention is used to monitor, evaluate and control the distribution transformer area based on a certain frequency, the dynamic imbalance of the three-phase system can be greatly reduced, and the power supply voltage quality of the distribution station area can be improved.

[0061] In a second embodiment of a transformer three-phase imbalance control method based on big data proposed by the present invention, based on the first embodiment, step S120 includes the following steps:

[0062] Step S210: The server averages the three-phase power values ​​of the distribution network users to obtain a power mean value P AV .

[0063] Step S220: The server compares the three-phase power values ​​of the distribution network users with the power mean P AV Subtract to get the phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 .

[0064] Step S230: The server calculates the power difference value P of the phase A based on the power difference value P of the phase A. A1 , B phase power difference P B1 and the C phase power difference P C1 Calculate the N-phase power P of the distribution networkN .

[0065] In the third embodiment of the transformer three-phase unbalance control method based on big data proposed by the present invention, based on the second embodiment, the server is based on the A phase power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 Calculate the N-phase power P of the distribution network N The calculation formula is:

[0066]

[0067] Where, P N is the N-phase power of the distribution network.

[0068] In a fourth embodiment of a transformer three-phase imbalance control method based on big data proposed by the present invention, based on the third embodiment, step S130 includes the following steps:

[0069] Step S410: The server determines the N-phase power P of the power distribution network. N Is it greater than the preset power limit value P? NX .

[0070] Specifically, the power limit value P in this embodiment is NX Preferably 20kW.

[0071] If so, step S420 is executed: the server determines that the distribution network meets the three-phase power adjustment conditions, controls the transformer, high-voltage switchgear and low-voltage switchgear of the distribution network to shut down, and resets the three-phase power value.

[0072] Specifically, if the N-phase power P of the distribution network N Greater than the preset power limit value P NX , the hardware circuit will be damaged due to overcurrent, and it is necessary to shut down the machine for protection and reset the three-phase power. N Less than or equal to the preset power limit value P NX , power monitoring is continued.

[0073] In a fifth embodiment of a transformer three-phase imbalance control method based on big data proposed by the present invention, based on the fourth embodiment, the three-phase voltage values ​​include a phase A voltage value, a phase B voltage value, and a phase C voltage value; step S140 includes the following steps:

[0074] Step S510: The server obtains the maximum value U among the voltage values ​​of phase A, phase B and phase C. MAX .

[0075] Step S520: The server averages the voltage values ​​of phase A, phase B, and phase C to obtain the average voltage value of the three phases U A .

[0076] Step S530: The server calculates the maximum value U among the voltage values ​​of phase A, phase B and phase C. MAX , and the three-phase voltage average value U A Calculate the three-phase imbalance Y of the distribution network Nb :

[0077]

[0078] Where Y Nb is the three-phase imbalance of the distribution network.

[0079] Specifically, this embodiment provides a method for calculating the three-phase imbalance Y of the distribution network. Nb Specific formula.

[0080] In a sixth embodiment of a transformer three-phase imbalance control method based on big data proposed by the present invention, based on the fifth embodiment, step S150 includes the following steps:

[0081] Step S610: The server calculates the three-phase imbalance Y of the distribution network Nb and the preset three-phase unbalance threshold Y NY Make a comparison.

[0082] Step S620: When Y Nb Greater than Y NY When the power distribution network is in a state of emergency, the server determines that phase switching management is required.

[0083] Specifically, in this embodiment, the three-phase imbalance threshold Y NY It is a preset value, which is related to the ability of the N-phase electrical equipment hardware (transformer) of the distribution network to withstand. Nb Less than or equal to Y NY , it means that the distribution network is currently normal and the three-phase power of the system does not need to be governed. Otherwise, the power imbalance value of each phase is obtained by calculating the three-phase imbalance rate to perform three-phase imbalance governance.

[0084] In a seventh embodiment of a transformer three-phase imbalance control method based on big data proposed by the present invention, based on the sixth embodiment, step S160 includes the following steps:

[0085] Step S710: The server determines the active power P of the phase A of the distribution network user based on the three-phase power value of the distribution network user. A , B phase active power P B and C phase active power PC .

[0086] Step S720: The server calculates the active power of phase A based on the active power P A , B phase active power P B , C phase active power P C , Phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P B1 Determine the phases that need load switching and the commutation capacity required for switching.

[0087] In an eighth embodiment of a method for controlling three-phase imbalance of a transformer based on big data proposed by the present invention, based on the seventh embodiment, step S720 includes the following steps:

[0088] Step S810: If P A >P B >P C The server determines that phase A and phase C are the phases that need load switching. The switching process is to select part of the single-phase load from phase A of the transformer and switch it to phase C of the transformer. The adjustment amount is

[0089] Step S820: If P A =P B >P C The server determines that phase A and phase B are the phases that need load switching. The switching process is to select part of the single-phase load from phase B of the transformer and switch it to phase C of the transformer. The adjustment amount is

[0090] Step S830: If P A >P B =P C The server determines that phase B and phase C are the phases that need load switching. The switching process is to select part of the single-phase load from phase A of the transformer and switch it to phase B or phase C of the transformer. The adjustment amount is

[0091] Specifically, the distribution substation should generally be equipped with multiple phase-changing switches, each of which is connected to a load of a certain capacity. To achieve uniform load distribution, it is necessary to partially switch the load of the heavy-load phase to the light-load phase. In theory, multiple rounds and multiple groups of switching are required to achieve load balance, but in actual projects, the load connected to each phase-changing switch is uncertain and does not necessarily meet the requirements of the adjustment formula. In order to quickly and easily determine and adapt the required phase-changing capacity, considering that the load phase-changing is carried out by the phase-changing switch under the command of the intelligent distribution terminal, its calculation should not be too complicated. At the same time, considering the continuous changes in load and the continuous switching of switches, it is proposed to perform switching only once per round, and to perform switching based on a comprehensive consideration of the relationship between the system imbalance adjustment and the load size.

[0092] In a ninth embodiment of a method for controlling three-phase imbalance of a transformer based on big data proposed by the present invention, based on the eighth embodiment, step S170 includes the following steps:

[0093] Step S910: the management module controls the initial numbering of each phase-changing switch to be numbered from large to small according to the current allowed phase-changing interval of each phase-changing switch.

[0094] Step S920: the management module controls the dynamic change time point of each phase-changing switch after each phase-changing switching. When the phase-changing switch that participated in the phase-changing switching for the last time changes, the number of the phase-changing switch is arranged after the other switches.

[0095] Step S930: The management module controls the dynamic change time point of each phase-changing switch after each phase-changing switching. The initial number of each phase-changing switch and the change number after each phase-changing switching are numbered from large to small according to the current allowed phase-changing interval time of each phase-changing switch.

[0096] Specifically, each commutation switch exists in the same distribution station. To ensure that the number of switch operations is similar, a ranking method is used to select the commutation switches. Specifically, the first n commutation switches are selected for load matching, and the remaining switches are not included in this matching. The switch that has just been operated is ranked last. This ensures a uniform distribution of the number of switch operations.

[0097] The present invention also proposes a transformer three-phase imbalance management system based on big data, which applies a transformer three-phase imbalance management method based on big data; the system includes a smart meter, a server and a management module: the smart meter and the management module are both communicatively connected to the server.

[0098] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0099] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are protected by the present invention.

Claims

1. A method for controlling three-phase imbalance of transformer based on big data, characterized in that: A transformer three-phase imbalance management system based on big data is applied; the system includes a smart meter, a server, and a management module; the smart meter and the management module are both communicatively connected to the server; the method includes: The smart meter collects three-phase power values ​​of users in the distribution network and sends them to the server; The server determines the power mean value P based on the three-phase power value of the distribution network user AV , and based on the three-phase power value and power mean P of the distribution network users AV Calculate the N-phase power P of the distribution network N ; The server is based on the N-phase power P of the power distribution network N Determine whether the distribution network meets the three-phase power adjustment conditions; If the three-phase power adjustment conditions are met, the server collects the three-phase voltage values ​​of the distribution network users in real time through the smart meter, and calculates the three-phase imbalance Y of the distribution network based on the three-phase voltage values ​​of the distribution network users. Nb ; The server calculates the three-phase imbalance Y of the power distribution network Nb Determine whether the distribution network needs phase switching management; If phase switching is required, the server determines the phase that needs load switching and marks it as the target phase, as well as the phase switching capacity required for switching and marks it as the target capacity; The server controls the startup of the management module to select a phase-changing switch whose access phase corresponds to the target phase and whose access load is adapted to the target capacity, thereby performing load switching.

2. The method for controlling three-phase imbalance of a transformer based on big data according to claim 1, characterized in that: The server determines the power mean value P based on the three-phase power value of the distribution network user AV , and based on the three-phase power value and power mean P of the distribution network users AV Calculate the N-phase power P of the distribution network N ,include: The server averages the three-phase power values ​​of the distribution network users to obtain a power mean value P AV ; The server compares the three-phase power values ​​of the distribution network users with the power mean P AV Subtract to get the phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 ; The server is based on the phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 Calculate the N-phase power P of the distribution network N .

3. The method for controlling three-phase imbalance of a transformer based on big data according to claim 2, characterized in that: The server is based on the phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P C1 Calculate the N-phase power P of the distribution network N The calculation formula is: Where, P N is the N-phase power of the distribution network.

4. The method for controlling three-phase imbalance of a transformer based on big data according to claim 3 is characterized in that: The server is based on the N-phase power P of the power distribution network N Determine whether the distribution network meets the three-phase power adjustment conditions, including: The server will determine the N-phase power P of the power distribution network N Is it greater than the preset power limit value P? NX ; If so, the server determines that the power distribution network meets the three-phase power adjustment conditions, controls the transformer of the power distribution network to shut down, and resets the three-phase power value.

5. The method for controlling three-phase imbalance of a transformer based on big data according to claim 4, characterized in that: The three-phase voltage value includes the A-phase voltage value, the B-phase voltage value and the C-phase voltage value; if the three-phase power adjustment condition is met, the server collects the three-phase voltage value of the distribution network user in real time through the smart meter, and calculates the three-phase imbalance Y of the distribution network based on the three-phase voltage value of the distribution network user Nb ,include: The server obtains the maximum value U among the voltage values ​​of phase A, phase B and phase C. MAX ; The server averages the voltage values ​​of phase A, phase B, and phase C to obtain the average voltage value of the three-phase voltage U A ; The server is based on the maximum value U among the A phase voltage value, the B phase voltage value and the C phase voltage value. MAX , and the three-phase voltage average value U A Calculate the three-phase imbalance Y of the distribution network Nb : Where Y Nb is the three-phase imbalance of the distribution network.

6. The method for controlling three-phase imbalance of a transformer based on big data according to claim 5, characterized in that: The server calculates the three-phase imbalance Y of the power distribution network Nb Determine whether the distribution network needs phase switching management, including: The server calculates the three-phase imbalance Y of the distribution network Nb and the preset three-phase unbalance threshold Y NY Make comparisons; When Y Nb Greater than Y NY When the power distribution network is in a state of emergency, the server determines that phase switching management is required.

7. The method for controlling three-phase imbalance of a transformer based on big data according to claim 6, characterized in that: If phase switching management is required, the server determines the phase that requires load switching and marks it as the target phase, as well as the phase switching capacity required for switching and marks it as the target capacity, including: The server determines the A-phase active power P of the distribution network user based on the three-phase power value of the distribution network user. A , B phase active power P B and C phase active power P C ; The server is based on the active power P of phase A A , B phase active power P B , C phase active power P C , Phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P B1 Determine the phases that need load switching and the commutation capacity required for switching.

8. The method for controlling three-phase imbalance of a transformer based on big data according to claim 7, characterized in that: The server is based on the active power P of phase A A , B phase active power P B , C phase active power P C , Phase A power difference P A1 , B phase power difference P B1 and the C phase power difference P B1 Determine the phases that need to be switched, and the switching capacity required when switching. include: If P A >P B >P C The server determines that phase A and phase C are the phases that need load switching. The switching process is to select part of the single-phase load from phase A and switch it to phase C. The adjustment amount is If P A =P B >P C The server determines that phase A and phase B are the phases that need load switching. The switching process is to select part of the single-phase load from phase B and switch it to phase C. The adjustment amount is If P A >P B =P C The server determines that phase B and phase C are the phases that need load switching. The switching process is to select part of the single-phase load from phase A and switch it to phase B or phase C. The adjustment amount is 9. The method for controlling three-phase imbalance of a transformer based on big data according to claim 8, characterized in that: The server controls the management module to start, so as to select a phase-changing switch whose access phase corresponds to the target phase and whose access load is adapted to the target capacity, thereby performing load switching, including: The management module controls the initial numbering of each phase-changing switch to be numbered from large to small according to the current allowed phase-changing interval of each phase-changing switch; The management module controls the dynamic change time point of each phase-changing switch after each phase-changing switching. When changing, the phase-changing switch that participated in the phase-changing switching for the last time is numbered after other switches; The management module controls the dynamic change time point of each phase-changing switch after each phase-changing switching. The initial number of each phase-changing switch and the change number after each phase-changing switching are both numbered from large to small according to the current allowed phase-changing interval time of each phase-changing switch.

10. A transformer three-phase imbalance management system based on big data, characterized in that: A method for controlling three-phase imbalance of a transformer based on big data is applied as described in any one of claims 1 to 9; the system includes a smart meter, a server and a control module: the smart meter and the control module are both communicatively connected to the server.

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