Low-voltage distribution network load imbalance adjustment benefit calculation method based on intelligent electric meter data

Abstract

The invention relates to a low-voltage distribution network load imbalance adjustment benefit calculation method based on intelligent electric meter data. And a Monte Carlo simulation method is adopted, the total cost saved by three-phase load imbalance after commutation optimization compared with the total cost saved by three-phase load imbalance before commutation optimization is calculated through multiple times of cycle simulation, and the average value of the total cost saved by three-phase load imbalance of multiple times of cycle simulation is output as a final result. According to the method, the total saved cost of three-phase load commutation optimization can be calculated, so that the superiority of load unbalance adjustment of the low-voltage distribution network based on commutation optimization is verified.

Description

Technical Field

[0001] The invention relates to a method for calculating the benefit of unbalanced load adjustment of a low-voltage distribution network based on smart meter data. Background Art

[0002] Three-phase imbalance is an important indicator for evaluating power quality. In an ideal power system, the three-phase voltage and current in the power grid are equal in magnitude and 120° in phase, so that the A, B, and C three-phase lines are in a balanced state. However, in actual operation, due to errors in the power system, uneven distribution of power load, constant changes in power load, and power components failing to achieve the ideal operating state, the three-phase lines will have inconsistent amplitudes of the three-phase voltage or current, or the phase difference of the three-phase voltage or current is not 120°, which we call three-phase imbalance.

[0003] The main reasons for the three-phase imbalance of the power distribution network are as follows:

[0004] (1) Due to the asymmetry of the components in the power generation, transformation, transmission and distribution links, or the existence of short circuits, disconnections and other faults in the power system, the system parameters are asymmetric, causing three-phase imbalance.

[0005] (2) The distribution of three-phase loads in the power distribution link is unreasonable. The distribution workers did not pay attention to controlling the balance of the three-phase loads when connecting the wires. The power and lighting circuits were mixed together, resulting in unbalanced three-phase loads.

[0006] (3) The electricity load is constantly changing, and temporary and seasonal electricity consumption are unstable. Such uncertainty in total amount and time will also lead to the occurrence of three-phase imbalance. Summary of the invention

[0007] The purpose of the present invention is to provide a method for calculating the benefits of load imbalance adjustment in a low-voltage distribution network based on smart meter data. The Monte Carlo simulation method is used to calculate the total cost saved by three-phase load imbalance after phase switching optimization compared with before phase switching optimization through multiple cycle simulations, and the average total cost saved by three-phase imbalance after multiple cycle simulations is output as the final result.

[0008] To achieve the above-mentioned purpose, the technical solution of the present invention is: a method for calculating the benefit of load imbalance adjustment of a low-voltage distribution network based on smart meter data, which adopts the Monte Carlo simulation method to calculate the total cost saved by the three-phase load imbalance after phase switching optimization compared with before phase switching optimization through multiple cycles of simulation, and outputs the average value of the total cost saved by the three-phase imbalance after multiple cycles of simulation as the final result.

[0009] In one embodiment of the present invention, the phase-changing optimization is to make the three-phase load of the low-voltage distribution network tend to be balanced by installing phase-changing switches.

[0010] In one embodiment of the present invention, before calculating the total cost saved by the phase-changing optimization compared with the three-phase load imbalance before the phase-changing optimization, the collected low-voltage distribution network user load data is partitioned to generate a low-voltage distribution network phase-changing optimization load database. For each area in the database, loads are randomly selected from the user loads in each area and randomly allocated to the three phases A, B, and C, and the total cost saved by the phase-changing optimization under the corresponding allocation mode compared with the three-phase load imbalance before the phase-changing optimization is calculated.

[0011] In an embodiment of the present invention, the user load data is single-phase load data.

[0012] In one embodiment of the present invention, the total cost saved due to three-phase load imbalance after commutation optimization compared to before commutation optimization includes additional reinforcement costs ARC and additional energy loss costs.

[0013] In one embodiment of the present invention, the additional reinforcement cost ARC is calculated as follows:

[0014]

[0015]

[0016]

[0017] ARC≈3k f DPIB f +k t DPIB t (4)

[0018] Among them, Asset f Main feeder reinforcement costs, Asset t is the transformer reinforcement cost, d is the discount rate, r is the load growth rate, for Phase power of each phase, DPIB t is the transformer unbalance, P N is the neutral power, DPIB f is the main feeder unbalance, U n is the rated voltage of the neutral line, P t is the transformer power, k f is the main feeder reinforcement cost after commutation optimization, k t Cost of transformer reinforcement after commutation optimization.

[0019] In one embodiment of the present invention, the additional energy loss cost AELC includes the energy loss caused by phase residual current and additional transformer copper loss.

[0020] In one embodiment of the present invention, the additional energy loss cost AELC is specifically calculated as follows:

[0021] 1) Transformer copper loss is the difference between the transformer copper loss in the three-phase balanced case and the transformer copper loss in the three-phase unbalanced case;

[0022] 2) Line loss: When the three phases are balanced, only the loss of the three phase line is considered; when the three phases are unbalanced, both the loss of the three phase line and the loss of the neutral line need to be considered;

[0023] The value of the additional energy loss cost AELC is:

[0024]

[0025] E t_i =E i -E trans (6)

[0026]

[0027]

[0028] I prc (t) = [I A 2 (t)+I B 2 (t)+I C 2 (t)-I A (t)I B (t)-I B (t)I C (t)-I A (t)I C (t)] 1 / 2 (9)

[0029] AELC=(E loss +E t_i )×π (10)

[0030] Among them, E loss is the energy loss caused by phase residual current, E t_i is the energy loss caused by the additional transformer copper loss, I(t is the balanced phase current at time t, I prc ( t ) is the phase residual current at time t, R n is the neutral line resistance, R ω is the transformer winding resistance, E i is the energy loss caused by the three-phase current, E trans To balance the energy loss caused by phase current, Nt is time t, and Δt is the actual running time of the line.

[0031] The present invention also provides a low-voltage distribution network load imbalance adjustment system based on smart meter data, including a memory, a processor, and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0032] The present invention also provides a computer-readable storage medium, on which computer program instructions that can be executed by a processor are stored. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0033] Compared with the prior art, the present invention has the following beneficial effects: the method of the present invention adopts the Monte Carlo simulation method, and through multiple cycles of simulation, calculates the total cost saved by the three-phase load imbalance after phase switching optimization compared with that before phase switching optimization, and outputs the average value of the total cost saved by the three-phase imbalance of multiple cycles of simulation as the final result. The method of the present invention can calculate the total cost saved by the three-phase load phase switching optimization, thereby verifying the superiority of the low-voltage distribution network load imbalance adjustment based on phase switching optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is the basic framework of the Monte Carlo simulation of the present invention.

[0035] Figure 2 Design a flow chart for the degree.

[0036] Figure 3 This is the 24-hour load data curve for all users in the area. DETAILED DESCRIPTION

[0037] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings.

[0038] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0039] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0040] The present invention provides a method for calculating the benefits of load imbalance adjustment in a low-voltage distribution network based on smart meter data. The method adopts the Monte Carlo simulation method and calculates the total cost saved by three-phase load imbalance after phase switching optimization compared with before phase switching optimization through multiple cycle simulations. The average value of the total cost saved by three-phase imbalance after multiple cycle simulations is output as the final result.

[0041] The following is the specific implementation process of the present invention.

[0042] like Figure 1 As shown, this embodiment provides a method for calculating the benefits of load imbalance adjustment of low-voltage distribution network based on smart meter data, and proposes a new Monte Carlo simulation algorithm to study the economic benefits that can be generated by the new scheme for three-phase load imbalance adjustment of low-voltage distribution network. The Monte Carlo simulation takes into account the transmission line loss and the core loss of the distribution transformer, and finally calculates the economic benefits of the new scheme through these losses.

[0043] 1. Method Overview

[0044] In order to conduct accurate economic benefit evaluation, complete time series user load data is required as input data. However, since the user data of my country's power system is not easily available, the present invention uses the 24-hour load data of 60 users in a certain area on X / X / 20XX to conduct economic benefit evaluation.

[0045] Figure 1 The basic principle of evaluating the economic benefits of a solution through Monte Carlo simulation is introduced, which includes three stages:

[0046] Phase 1: Import the collected low-voltage distribution network user load data into the Matlab program, and partition all loads according to the third partitioning result of the scheme.

[0047] The second stage: Generate a load database for the phase-changing optimization program of the low-voltage distribution network. For each area in the database, randomly select loads from the user loads in each area and randomly distribute them to the three phases A, B, and C, and calculate the losses caused by the three-phase imbalance of the distribution network under this distribution mode. Use Monte Carlo simulation to simulate the above distribution mode in a loop, and repeat this process 100 times to obtain more objective and applicable results.

[0048] Phase 3: The results of the second phase are different calculation results under each allocation mode. The results of these 100 simulations are compared and calculated, and the average value is obtained as the final cost savings of the plan. This avoids excessive deviation between a certain allocation and the actual cost, and is more valuable for reference.

[0049] 2. Low voltage network system and load data

[0050] In the low-voltage distribution system, most circuits are used for a mixture of power and lighting loads. Among these loads, most are single-phase loads, and only a small part is three-phase loads. Since the currents of the three-phase loads connected to the A, B, and C phases are basically equal, the imbalance of the three-phase loads of the system will not be affected. However, the single-phase load can only be connected to one of the three phases A, B, and C, so there is a load distribution problem when distributing the power load. This unbalanced distribution will lead to an imbalance in the three-phase load, affecting the stability and operating efficiency of the distribution system, and causing unnecessary economic losses.

[0051] Taking the above factors into consideration, for the convenience of research, the user load data used in the simulation verification process of the present invention are all single-phase load data, so that the research can be carried out more efficiently.

[0052] 3. Calculation of three-phase unbalanced cost

[0053] In the phase-changing optimization scheme, the three-phase load of the low-voltage distribution network was unbalanced before the phase-changing switch was installed, resulting in a serious imbalance in the three-phase current and an increase in the current flowing through the neutral line. After the reconstruction of the substation, the three-phase load became balanced under the adjustment of the phase-changing switch, so the three-phase current was also close to a balanced state, and the current flowing through the neutral line was very small. The losses in the substation mainly include additional reinforcement costs and additional energy loss costs. The loss costs caused by three-phase imbalance will be analyzed below.

[0054] 3.1. Additional reinforcement costs

[0055] In order to measure the severity of phase power imbalance, an indicator is usually used: power imbalance. The power imbalance index is a guiding indicator for phase switching and an important factor in estimating the additional reinforcement cost ARC. The value of ARC can be calculated from formulas 1 to 4:

[0056]

[0057]

[0058]

[0059] ARC≈3k f DPIB f +k t DPIB t (4)

[0060] Asset f Main feeder reinforcement costs, Asset t is the transformer reinforcement cost, d is the discount rate, r is the load growth rate, for Phase power of each phase, DPIB t is the transformer unbalance, P N is the neutral power, DPIB f is the main feeder unbalance, U n is the rated voltage of the neutral line, P t is the transformer power, k f To optimize the cost of main feeder reinforcement, k t The cost of transformer reinforcement after optimization.

[0061] 3.2. Additional energy loss costs

[0062] The energy loss caused by three-phase load unbalance includes the energy loss caused by phase residual current and additional transformer copper loss. The present invention considers the TT grounding system and calculates the energy loss caused by phase residual current. The transformer copper loss is the difference between the transformer copper loss in the balanced case and the transformer copper loss in the unbalanced case.

[0063] (1) Transformer loss

[0064] Transformer loss is mainly composed of iron loss and copper loss. Iron loss is mainly composed of magnetic materials (iron core, etc.) in the transformer and basically does not change. Copper loss is the loss caused by the heating of the transformer winding caused by the current flowing through the transformer winding, which changes with the current. Therefore, this article only considers the changes in copper loss when studying the loss of the transformer under three-phase unbalanced conditions. The calculation method of transformer copper loss is shown in formula 3-5:

[0065] P cu =(I A 2 +I B 2 +I C 2 )R1+(I a 2 +I b 2 +I c 2 )R2 (5)

[0066] In the formula, I A ,I B ,I C are the currents flowing through the A, B, and C phase windings on the primary side of the transformer, R1 is the equivalent resistance value of the primary winding; I a ,I b ,I c They are the currents flowing through the a, b, and c phase windings on the secondary side of the transformer, and R2 is the equivalent resistance of the secondary winding.

[0067] (2) Line loss

[0068] Most of the low-voltage distribution networks in my country use three-phase four-wire wiring. When the three-phase load is balanced, the three-phase current also tends to be balanced. At this time, the current flowing through the neutral line is very small or even zero, so the loss on the neutral line is also very small. To calculate the line loss, you only need to consider the loss of the three-phase line. When the three-phase load in the substation is unbalanced, the three-phase current will also become unbalanced, causing a larger current to flow through the neutral line, resulting in additional losses. Therefore, to calculate the line loss at this time, you need to consider both the three-phase line loss and the neutral line loss. The overhead distribution line model selected for this substation is LJ35, with a resistivity of 0.823Ω / km. From the substation wiring diagram, it can be calculated that the distribution line of the entire substation is about 2749.5 meters long. The line loss calculation of the three-phase four-wire system is shown in Formula 3-6:

[0069] P l =(I A 2 +I B 2 +I C 2 +I N 2 )R l (6)

[0070] In the formula, I A ,I B ,I C ,I N are the three-phase current of the substation system and the current flowing through the neutral line, R l It is the total resistance value of the distribution line in the substation.

[0071] The value of AELC can be calculated from equations 7 to 12:

[0072]

[0073] E t_i =E i -E trans (8)

[0074]

[0075]

[0076] I prc (t) = [I A 2 9t)+I B 2 9t)+I C 2 9t)-I A 9t)I B (t)-I B (t)IC (t)-I A (t)I C (t)] 1 / 2 (11)

[0077] AELC=(E loss +E t_i )×π (12)

[0078] E loss is the energy loss caused by phase residual current, E t_i is the energy loss caused by the additional transformer copper loss, I(t) is the balanced phase current at time t, and I prc (t) is the phase residual current at time t, R n is the neutral line resistance, R ω is the transformer winding resistance, E i is the energy loss caused by the three-phase current, E trans To balance the energy loss caused by phase current, N t is time t, and Δt is the actual running time of the line.

[0079] 3.3 Total cost caused by three-phase imbalance

[0080] The total cost caused by three-phase imbalance is the sum of the additional reinforcement cost and the additional energy loss cost, as shown in Formula 13:

[0081] TIC=ARC+AELC(13)

[0082] Table 1 shows some indicators used in formulas 1 to 11:

[0083] Table 1 Index annotation table

[0084]

[0085]

[0086] 4. Example simulation

[0087] Combining the above low voltage distribution network commutation optimization scheme and Monte Carlo simulation, write a Matlab program to Figure 2 The low-voltage distribution network shown in the figure is partitioned by simulation to verify the economic feasibility of the commutation optimization scheme.

[0088] 4.1 Programming ideas

[0089] Read the collected user load data, extract the user load data into the Matlab database, and then partition the user load data in the database. The partitioning is strictly carried out according to the phase-changing optimization plan. Create a Monte Carlo simulation loop and set the number of loops to 100. In each Monte Carlo simulation loop, randomly extract user load data from each partition after the real-time load partition and randomly assign it to the three phases A, B, and C. Calculate the total cost of three-phase unbalance that can be saved each year in the low-voltage distribution network after the phase-changing switch is installed. After simulating the above random allocation cycle 100 times, end the loop, calculate the average total cost of three-phase unbalance and output the final result.

[0090] Program design flow chart Figure 2 shown.

[0091] 4.2 Monte Carlo simulation

[0092] 4.2.1 User load data processing

[0093] Since the obtained user load data is stored in a separate .xlsx file in the form of Excel table data, it is necessary to extract the obtained user load data before partitioning it. Here, the xlsread function is used to read the user load data in the .xlsx file, and then the read user load data is saved in the Matlab database for subsequent use. Since the system cannot automatically match the original data file specifications when directly saving the data, it is necessary to define an additional matrix to save the user load data. In addition, the size of the matrix needs to be set in advance before defining the matrix.

[0094] In order to more vividly see the changes in user load data over time, use the plot function to plot all user load data into a line graph, with the horizontal axis being time and the vertical axis being the size of the user load data. Figure 3 This is the line graph of user load data.

[0095] 4.2.2 Monte Carlo simulation cycle

[0096] Before performing a Monte Carlo simulation cycle, you need to set the number of cycles, which is set to 100 here to obtain more objective and applicable results. If the number of simulations is set to 30 or 50, it cannot cover the possible situations of the entire low-voltage distribution network; and if the number of simulations is set to 200 or 300, the results obtained are very similar to those obtained by simulating 100 times. Therefore, choosing 100 simulations can display better results with a shorter program running time.

[0097] After setting the appropriate number of cycles, users in each area are randomly assigned to phases A, B, and C. Here, the randperm function is used to randomly shuffle the order of users in the area and assign them to phases A, B, and C. After the assignment is completed, the three-phase current and power are calculated, which are subsequently used to calculate the three-phase unbalanced cost.

[0098] 4.2.3. Solution of three-phase unbalanced cost

[0099] After the above load distribution and three-phase current and power solution are completed, the total cost of three-phase unbalance that can be saved by the commutation optimization scheme in one year is calculated. According to equations 1 to 13, the total cost of three-phase unbalance is solved by the algorithm in the Matlab program. During the calculation process, some parameters used are shown in Table 2:

[0100] Table 2 Project parameters

[0101]

[0102] 4.2.4. Simulation result processing

[0103] The results obtained from the previous calculations cannot be used directly, because the results of the 100 simulations are not exactly the same, and it is impossible to directly see how much the total cost of three-phase imbalance can be saved by the commutation optimization solution in a year. Therefore, it is necessary to average all the simulation results, so that the results obtained avoid excessive deviations between a certain allocation and the actual situation, and are more valuable for reference.

[0104] 4.3 Simulation results and analysis

[0105] In order to ensure the correctness and rigor of the simulation results, a large number of cyclic verifications were carried out in this simulation. First, the user load was partitioned, and each partition was partitioned by electrical distance in strict accordance with the phase-changing optimization scheme; then each partition was randomly assigned, and the total unbalanced cost under the corresponding assignment was calculated, and the Monte Carlo simulation cycle was repeated 100 times; finally, the results were summarized and the average was calculated.

[0106] The Matlab program shows that the total unbalanced cost that can be saved by the commutation optimization scheme is 46,800 yuan per year, of which the transformer and line cost savings are 16,800 yuan. The economic benefits of the low-voltage distribution network commutation optimization scheme are shown in Table 3:

[0107] Table 3 Economic Benefits of Phase Commutation Optimization Scheme

[0108]

[0109] In summary, after the implementation of the low-voltage distribution network phase-change optimization plan, the substation can save 46,800 yuan each year. Assuming that the average service life of the electrical equipment in the substation is 10 years, the total cost saved in 10 years is 468,000 yuan. The phase-change optimization plan has good economic benefits.

[0110] The present invention also provides a low-voltage distribution network load imbalance adjustment system based on smart meter data, including a memory, a processor, and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0111] The present invention also provides a computer-readable storage medium, on which computer program instructions that can be executed by a processor are stored. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0112] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0113] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0116] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. A method for calculating the benefits of load imbalance adjustment in a low-voltage distribution network based on smart meter data, characterized in that: The Monte Carlo simulation method is used to calculate the total cost saved by three-phase load imbalance after phase switching optimization through multiple cycles of simulation. The average total cost saved by three-phase load imbalance after multiple cycles of simulation is output as the final result.

2. The method for calculating the benefit of low-voltage distribution network load imbalance adjustment based on smart meter data according to claim 1 is characterized in that: Phase-changing optimization is to make the three-phase load of the low-voltage distribution network balanced by installing phase-changing switches.

3. The method for calculating the benefit of low-voltage distribution network load imbalance adjustment based on smart meter data according to claim 1 is characterized in that: Before calculating the total cost saved by the phase-changing optimization compared with the three-phase load imbalance before the phase-changing optimization, the collected low-voltage distribution network user load data is partitioned to generate a low-voltage distribution network phase-changing optimization load database. For each area in the database, loads are randomly selected from the user loads in each area and randomly allocated to the three phases A, B, and C. The total cost saved by the phase-changing optimization under the corresponding allocation mode compared with the three-phase load imbalance before the phase-changing optimization is calculated.

4. The method for calculating the benefit of load imbalance adjustment of low-voltage distribution network based on smart meter data according to claim 3 is characterized in that: The user load data is single-phase load data.

5. The method for calculating the benefit of low-voltage distribution network load imbalance adjustment based on smart meter data according to claim 1 is characterized in that: The total cost saved by the three-phase load imbalance after commutation optimization compared with that before commutation optimization includes the additional reinforcement cost ARC and the additional energy loss cost.

6. The method for calculating the benefit of load imbalance adjustment of low-voltage distribution network based on smart meter data according to claim 5 is characterized in that: The additional reinforcement cost ARC is calculated as follows: ARC≈3k f DPIB f +k t DPIB t (4) Among them, Asset f Main feeder reinforcement costs, Asset t is the transformer reinforcement cost, d is the discount rate, r is the load growth rate, for Phase power of each phase, DPIB t is the transformer unbalance, P N is the neutral power, DPIB f is the main feeder unbalance, U n is the rated voltage of the neutral line, P t is the transformer power, k f is the main feeder reinforcement cost after commutation optimization, k t Cost of transformer reinforcement after commutation optimization.

7. The method for calculating the benefit of load imbalance adjustment of low-voltage distribution network based on smart meter data according to claim 5 is characterized in that: The additional energy loss cost AELC includes the energy loss caused by phase residual current and additional transformer copper losses.

8. The method for calculating the benefit of load imbalance adjustment of low-voltage distribution network based on smart meter data according to claim 5 is characterized in that: The additional energy loss cost AELC is calculated as follows: 1) Transformer copper loss is the difference between the transformer copper loss in the three-phase balanced case and the transformer copper loss in the three-phase unbalanced case; 2) Line loss: When the three phases are balanced, only the loss of the three phase line is considered; when the three phases are unbalanced, both the loss of the three phase line and the loss of the neutral line need to be considered; The value of the additional energy loss cost AELC is: AND t_i =And i -AND trans (6) I prc (t)=[I A 2 (t)+I B 2 (t)+I C 2 (t)-I A (t(I B (t)-I B (t)I C (t)-I A (t)I C (t)] 1 / 2 (9) AELC=(E loss +E t_i )×π (10) Among them, E loss is the energy loss caused by phase residual current, E t_i is the energy loss caused by the additional transformer copper loss, I(t) is the balanced phase current at time t, and I prc (t) is the phase residual current at time t, R n is the neutral line resistance, R ω is the transformer winding resistance, E i is the energy loss caused by the three-phase current, E trans To balance the energy loss caused by phase current, N t is time t, and Δt is the actual running time of the line.

9. A low voltage distribution network load imbalance adjustment system based on smart meter data, characterized in that: The method comprises a memory, a processor and computer program instructions stored in the memory and executable by the processor. When the processor executes the computer program instructions, the method steps as claimed in any one of claims 1 to 8 can be implemented.

10. A computer-readable storage medium storing computer program instructions that can be executed by a processor, wherein when the processor executes the computer program instructions, the method steps according to any one of claims 1 to 8 can be implemented.

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