Three-phase imbalance load adjustment method, device and equipment and storage medium

Abstract

The invention discloses a three-phase imbalance load adjustment method, device and equipment and a storage medium. The method comprises the following steps: acquiring three-phase current data of a target transformer area in a preset time period; according to the three-phase current data, the similarity between every two-phase current curves in each period is determined, and the preset time period comprises a plurality of periods. And according to the similarity between the current curves of every two phases in each period in the preset time period, judging whether the target transformer area is suitable for load adjustment or not. And under the condition that the target transformer area is suitable for load adjustment, constructing a three-phase total electricity consumption function of the target transformer area. According to the method, an optimization algorithm is utilized to perform multi-target optimization on a three-phase total electricity consumption function so as to determine a load adjustment strategy, targets of multi-target optimization comprise the minimum number of adjusted users and the minimum three-phase electricity consumption unbalance degree, and judgment of the applicability of the adjustment method and determination of the adjustment strategy are realized. The efficiency and the accuracy of three-phase imbalance adjustment are greatly improved, so that the influence on a user is reduced.

Description

Technical Field

[0001] The present invention relates to the field of electric power systems, and in particular to a three-phase unbalanced load adjustment method, device, equipment and storage medium. Background Art

[0002] During peak load periods, three-phase imbalance is prone to occur in each substation in the power system, which poses a great challenge to the operation and maintenance of the power system.

[0003] Adjusting the power phase of single-phase users in the substation is a common method to solve the three-phase imbalance problem. In the prior art, the operation and maintenance personnel are often relied on to judge the three-phase imbalance and make corresponding adjustments. Such an adjustment method is not only inefficient and inaccurate, but also has a great impact on users. Summary of the invention

[0004] The present invention provides a three-phase unbalanced load adjustment method, device, equipment and storage medium to improve the efficiency and accuracy of three-phase unbalanced adjustment, thereby reducing the impact on users.

[0005] According to one aspect of the present invention, a method for adjusting a three-phase unbalanced load is provided, the method comprising:

[0006] Obtain three-phase current data of the target area within a preset time period;

[0007] Determine the similarity between each two-phase current curve in each cycle according to the three-phase current data, wherein the preset time period includes a plurality of the cycles;

[0008] Determining whether the target substation is suitable for load adjustment according to the similarity between the current curves of each two phases in each of the cycles in the preset time period;

[0009] In the case where the target area is suitable for load adjustment, constructing a three-phase total power consumption function of the target area;

[0010] The three-phase total power consumption function is optimized by a multi-objective optimization algorithm to determine a load adjustment strategy, wherein the objectives of the multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption.

[0011] Optionally, the obtaining of three-phase current data of the target substation within a preset time period includes:

[0012] In each of the cycles of the preset time period, real-time three-phase current data of the target substation is collected once every unit time period;

[0013] All the real-time three-phase current data are screened and processed according to the load rate and the three-phase imbalance corresponding to the real-time three-phase current data.

[0014] Optionally, the screening and processing of all the real-time three-phase current data in the period according to the load rate and the three-phase imbalance corresponding to the real-time three-phase current data includes:

[0015] Calculating the load rate and the three-phase imbalance corresponding to the real-time three-phase current data;

[0016] The real-time three-phase current data corresponding to the load rate being higher than the preset load rate and the three-phase imbalance being higher than the preset imbalance is screened out as valid data.

[0017] Optionally, determining the similarity between each two-phase current curves in each cycle according to the three-phase current data includes:

[0018] Based on the three-phase current data, construct a time series matrix of each two-phase current in the cycle;

[0019] On the basis of the time series matrix, a dynamic time warping algorithm is used to obtain a dynamic warping distance between the corresponding two-phase currents as the similarity between the two-phase current curves.

[0020] Optionally, judging whether the target substation is suitable for load adjustment according to the similarity between the current curves of each two phases in each cycle in the preset time period includes:

[0021] Comparing the similarity between each two-phase current curve in the cycle, and determining the maximum similarity phase of the cycle;

[0022] Determine a reference relative value corresponding to the preset time period according to the number of times each relative value within the preset time period is repeatedly determined as the maximum similar relative value;

[0023] The reference relative repetition in the preset time period is determined as the number of times of the maximum similar relative, and compared with the number of unbalanced cycles in the preset time period to obtain the maximum similarity ratio of the preset time period;

[0024] When the maximum similarity ratio exceeds a preset ratio, it is determined that load adjustment is applicable to the target area.

[0025] Optionally, constructing the three-phase power consumption function of the target substation includes:

[0026] Constructing a power consumption matrix of all the single-phase users in the target substation in a single cycle and a corresponding power consumption phase sequence matrix;

[0027] The power consumption matrix and the power phase sequence matrix are used to express the three-phase total power consumption function of the target substation.

[0028] Optionally, the optimization algorithm includes a multi-objective genetic algorithm.

[0029] According to another aspect of the present invention, there is provided a three-phase unbalanced load adjustment device, the device comprising a data acquisition module, a similarity determination module, an applicability judgment module, a function construction module and a strategy determination module;

[0030] The data acquisition module is used to acquire the three-phase current data of the target area within a preset time period;

[0031] The similarity determination module is used to determine the similarity between each two-phase current curve in each cycle according to the three-phase current data, wherein the preset time period includes a plurality of the cycles;

[0032] The applicability judgment module is used to judge whether the target area is suitable for load adjustment according to the similarity between the current curves of each two phases in each cycle in the preset time period;

[0033] The function construction module is used to construct a three-phase total power consumption function of the target area when the target area is suitable for load adjustment;

[0034] The strategy determination module is used to perform multi-objective optimization on the three-phase total power consumption function using an optimization algorithm to determine a load adjustment strategy, wherein the objectives of the multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption.

[0035] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0036] at least one processor; and

[0037] a memory communicatively connected to the at least one processor; wherein,

[0038] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the three-phase unbalanced load adjustment method described in any embodiment of the present invention.

[0039] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the three-phase unbalanced load adjustment method described in any embodiment of the present invention when executed.

[0040] In the three-phase unbalanced load adjustment method, device, equipment and storage medium provided by the present application, the method obtains the three-phase current data of the target substation within a preset time period. According to the three-phase current data, the similarity between each two-phase current curve in each cycle is determined, and the preset time period includes multiple cycles. According to the similarity between each two-phase current curve in each cycle in the preset time period, it is judged whether the target substation is suitable for load adjustment. In the case where the target substation is suitable for load adjustment, a three-phase total power consumption function of the target substation is constructed. The three-phase total power consumption function is optimized by a multi-objective optimization algorithm to determine the load adjustment strategy. The objectives of the multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption, thereby realizing the judgment of the applicability of the adjustment method and the determination of the adjustment strategy, greatly improving the efficiency and accuracy of the three-phase imbalance adjustment, thereby reducing the impact on users.

[0041] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1 A schematic flow chart of a three-phase unbalanced load adjustment method provided by an embodiment of the present invention;

[0044] Figure 2 A flow chart of another method for adjusting three-phase unbalanced load provided by an embodiment of the present invention;

[0045] Figure 3 A schematic diagram of the structure of a three-phase unbalanced load adjustment device provided by an embodiment of the present invention;

[0046] Figure 4 A schematic diagram of the structure of an electronic device that can be used to implement an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0048] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0049] As described in the background technology, adjusting the electricity phase of single-phase users in the substation is a common method to solve the three-phase imbalance problem. In the prior art, the operation and maintenance personnel are often relied on to make judgments and corresponding adjustments to the three-phase imbalance. Such an adjustment method not only has low efficiency and accuracy, but also has a great impact on users. The inventors of this application have found that the adjustment method in the prior art mainly relies on staff, which is inefficient and has high labor costs. In addition, the adjustment method is greatly affected by the instantaneous value of the current and the time of measurement. If the accuracy of determining the user who needs phase adjustment is insufficient, it will lead to multiple load adjustments and increase the number of power outages. In addition, when the method in the prior art is used for adjustment, the judgment and adjustment amount are generally determined only based on the three-phase outlet current of the substation, and the power and meter data are not used for reference. It is difficult to reflect the overall level of load imbalance in the substation, resulting in poor adjustment effect.

[0050] Based on this, the present invention proposes a three-phase unbalanced load adjustment method, which can be applicable to situations where it is necessary to judge the three-phase imbalance and adjust the load of the substation in the power system. The method can be executed by a three-phase unbalanced load adjustment device, and the three-phase unbalanced load adjustment device can be implemented in the form of hardware and / or software. The three-phase unbalanced load adjustment device can be configured in the automatic operation and maintenance management system of the power system. Figure 1 A flow chart of a three-phase unbalanced load adjustment method provided by an embodiment of the present invention is shown in FIG. Figure 1 , the three-phase unbalanced load adjustment methods include:

[0051] S101, obtaining three-phase current data of a target substation within a preset time period.

[0052] Specifically, the target substation refers to the power supply range of the target transformer in the power system that needs to be adjusted for three-phase imbalance. The target substation includes the high-voltage incoming line, low-voltage outgoing line and the user area connected to the target transformer. For example, a residential community may be powered by a transformer of a specific capacity, and the community and the surrounding area powered by the transformer constitute a substation. The preset time period is a time period including multiple power supply cycles, wherein the power supply cycle refers to a unit time period in which the power supply data of the substation changes periodically. For example, when the cycle is one day, the preset time period may be one month or more months including multiple cycles. The three-phase current data refers to the three-phase power supply current data of the transformer in the target substation, which can be either continuously detected data or interval collected data. For example, the three-phase current data may include a group of three-phase currents collected every 25 minutes, and a group of three-phase currents includes corresponding A-phase current, B-phase current and C-phase current. The current data can be collected using metering facilities such as ammeters set on the power supply line, and then reported to the substation management system or the three-phase unbalanced load adjustment device.

[0053] S102: Determine the similarity between every two-phase current curves in each cycle according to the three-phase current data.

[0054] Specifically, the preset time period includes multiple cycles. According to the three-phase current data corresponding to the cycle, the current curve of each phase of the target substation in the cycle can be drawn, with the horizontal axis of the curve being time and the vertical axis being the corresponding phase current. The similarity between current curves refers to the closeness of the shape, trend and numerical distribution of the two-phase current in a substation over time, which can be determined based on the correlation coefficient, Euclidean distance or minimum cumulative distance of the two curves.

[0055] Exemplarily, taking the correlation coefficient as an example, for a two-phase current curve, the two-phase current value at each moment in the cycle can be regarded as a variable, and the correlation coefficient between the two-phase current curves at each moment is calculated and then accumulated. The larger the accumulated result of the correlation coefficient, the higher the similarity between the two-phase current curves. Taking the Euclidean distance as an example, for a two-phase current curve, the current values ​​at different time points in the cycle can be composed into vectors, and the Euclidean distance between the corresponding two vectors on the two-phase current curve at each time is calculated and accumulated. The smaller the accumulated result is, the higher the similarity between the two-phase current curves. Taking the minimum cumulative distance as an example, a path from the upper left corner to the lower right corner of the matrix is ​​found through the dynamic programming method, so that the cumulative distance on the path is the smallest. The calculation of the cumulative distance takes into account the distance between the current point and the previous point and the minimum cumulative distance to the previous point. The final minimum cumulative distance is the DTW distance of the two current curves. The smaller the distance, the higher the similarity.

[0056] S103: judging whether the target substation is suitable for load adjustment according to the similarity between the current curves of each two phases in each cycle in the preset time period.

[0057] Specifically, to determine whether the target substation is suitable for load adjustment, it is first necessary to determine whether the relative phases with the highest similarity in each period within a preset time period are highly concentrated in a certain relative phase, where the relative phases include AB, BC, and AC. If so, the target substation is suitable for three-phase unbalance adjustment by means of load adjustment, otherwise it is not suitable. The degree of concentration can be quantified by the number or proportion of each relative phase determined to have the highest similarity within a preset time period. The number or proportion is compared with the corresponding threshold value. If it is higher than the corresponding threshold value, it is determined that the target substation is suitable for load adjustment, otherwise it is determined that the target substation is not suitable for load adjustment and the process of this method ends.

[0058] S104. When load adjustment is applicable to the target substation, construct a three-phase total power consumption function of the target substation.

[0059] Specifically, the three-phase total power function is a relationship function of the three-phase total power of the unit cycle of the target area with respect to the power consumption data of each single-phase user, wherein the power consumption data of the single-phase user may include the user's single-cycle power consumption and power phase sequence. The single-cycle power consumption is the cumulative amount of the total power consumption of the single-phase user in a single cycle, which can be obtained by averaging the single-cycle historical power consumption of each unidirectional user in the target area. The power phase sequence corresponds to the single-cycle power consumption, which is the power phase sequence in the process of the single-phase user consuming the single-cycle power consumption, which can be A phase, B phase or C phase. The single-cycle power consumption of each user with the power phase sequence of A phase is accumulated, and the total power consumption of A phase in the target area in a single cycle can be expressed. Similar to phase A, the single-cycle power consumption of each user with the power phase sequence of B phase is accumulated, and the total power consumption of B phase in the target area in a single cycle can be expressed. The single-cycle power consumption of each user with the power phase sequence of C phase is accumulated, and the total power consumption of C phase in the target area in a single cycle can be expressed.

[0060] S105. Perform multi-objective optimization on the three-phase total power consumption function using an optimization algorithm to determine a load adjustment strategy.

[0061] Specifically, the optimization algorithm is an algorithm for finding the optimal solution to the problem. Exemplarily, the optimization algorithm may include at least one of the heuristic algorithms such as ant colony algorithm, simulated annealing method and neural network. The objectives of multi-objective optimization include the minimum number of adjusted users and the minimum imbalance of three-phase power consumption. Load adjustment refers to the operation of balancing each corresponding load by adjusting the power phase sequence of each single-phase user in the target area. The load adjustment strategy refers to the specific adjustment method of the power phase sequence of each single-phase user in the target area. Exemplarily, the load adjustment strategy may include adjusting the power consumption of the user numbered xxx from A phase to B phase, the user numbered xxx from A phase to C phase, the user numbered xxx from B phase to C phase, the user numbered xxx from B phase to A phase, the user numbered xxx from C phase to A phase, and the user numbered xxx from C phase to B phase. Based on the three-phase total power consumption function, two objective functions are expressed, namely the function of the number of adjusted users and the function of the imbalance of three-phase power consumption. The variable of the three-phase total power consumption function is determined as the power phase sequence of each single-phase user in the target substation, and the optimization algorithm is used to iteratively calculate the two objective functions to obtain the adjusted power phase sequence of the single-phase user. The adjusted power phase sequence of each single-phase user is compared with its corresponding initial power phase sequence to determine the load adjustment strategy for the entire target substation.

[0062] In the three-phase unbalanced load adjustment method provided in the present embodiment, the three-phase current data of the target substation within a preset time period is obtained. Based on the three-phase current data, the similarity between each two-phase current curve in each cycle is determined, and the preset time period includes multiple cycles. Based on the similarity between each two-phase current curve in each cycle in the preset time period, it is judged whether the target substation is suitable for load adjustment. In the case where the target substation is suitable for load adjustment, a three-phase total power consumption function of the target substation is constructed. The three-phase total power consumption function is optimized by a multi-objective optimization algorithm to determine the load adjustment strategy. The objectives of the multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption, thereby realizing the judgment of the applicability of the adjustment method and the determination of the adjustment strategy, greatly improving the efficiency and accuracy of the three-phase imbalance adjustment, thereby reducing the impact on users.

[0063] Figure 2 A flow chart of another method for adjusting a three-phase unbalanced load provided by an embodiment of the present invention is provided. Figure 2 , the three-phase unbalanced load adjustment methods include:

[0064] S201. In each cycle of a preset time period, real-time three-phase current data of a target substation is collected once every unit time period.

[0065] Specifically, the unit time period is a time period within a cycle, and each cycle is composed of multiple unit times. For example, in the case of a cycle of 1 day, the unit time can be 25 minutes. Then, in the process of collecting real-time three-phase current, it is necessary to collect it every 25 minutes. A 1-day cycle requires 96 sets of current data to be collected at equal intervals, so 96*30 sets of data can be collected within the preset time period of a month (taking a month as 30 days as an example). The real-time three-phase current data collected each time is a set of real-time current data, which includes the A-phase current, B-phase current and C-phase current of the target substation. Then the real-time three-phase current data of one cycle can be expressed in a matrix as: A-phase current I A =[I a1 ,I a2 ,I a3 ...I a96 ]、B phase current I B =[I b1 ,I b2 ,I b3 ...I b96 ] and C phase current I C =[I c1 ,I c2 ,I c3 ...I c96 ], where ABC letters represent the phase corresponding to the current, and the numbers after the letters represent the data sequence number.

[0066] S202: Screen and process all real-time three-phase current data according to the load rate and three-phase imbalance corresponding to the real-time three-phase current data.

[0067] Specifically, before screening, unbalanced cycles can be selected from a preset time period based on three-phase current data or operation and maintenance monitoring instructions, wherein the operation and maintenance monitoring instructions can indicate whether each cycle is balanced. Exemplarily, the standard for selecting unbalanced cycles based on three-phase current data can be to regard the cycle in which the three-phase unbalance exceeds the preset unbalance and the duration of the unbalance exceeds 40% as an unbalanced cycle. For example, if there are 12 days in a preset time period of a month when the three-phase unbalance of the target substation exceeds the preset unbalance, and the duration of the three-phase unbalance exceeding the preset unbalance on each of these 12 days is greater than 9.6 hours, then it can be determined that these 12 days are all unbalanced cycles.

[0068] Then, the real-time three-phase current data corresponding to the unbalanced period is screened. The screening process refers to screening out the current data with sufficiently high load rate and three-phase imbalance, so as to provide data support for subsequent judgment and strategy determination. The load rate and three-phase imbalance of the preset substation can be calculated based on the three-phase current data and its corresponding voltage data. At least two types of data are excluded in the screening process. One is the data corresponding to the low load rate. Such data is generated by the electricity consumption of a small number of users and is meaningless for the three-phase imbalance adjustment. For example, the screening standard of the load rate can be greater than or equal to 60%, and the real-time three-phase current data with a load rate less than or equal to 60% is screened out as a whole group; the other is the data corresponding to the low three-phase imbalance. Such data does not have a prominent three-phase imbalance problem and cannot be used as reference data. For example, the screening standard of the imbalance can be greater than 25%, and the three-phase current data with an imbalance less than or equal to 25% is screened out as a whole group. Exemplarily, according to the real-time three-phase current data corresponding to the cycle of three-phase imbalance, the load rate and three-phase imbalance corresponding to the cycle are calculated. The load rate can be equal to the ratio of the load actually borne by the transformer in the substation to its capacity; the three-phase imbalance is equal to the difference between the maximum phase current and the minimum phase current in the three-phase current data divided by the maximum phase current. The real-time three-phase current data with a corresponding load rate higher than the preset load rate and a corresponding three-phase imbalance greater than the preset imbalance is screened out as valid data.

[0069] S203: Based on the three-phase current data, construct a time series matrix of each two-phase current in the cycle.

[0070] Specifically, based on the remaining valid data screened in step S202, the valid data can be represented by a time series matrix as follows: A phase current I A =[I a1 ,I a2 ,I a3...I ax ]、B phase current I B =

[0071] [I b1 ,I b2 ,I b3 ...I bx ] and C phase current I C =[I c1 ,I c2 ,I c3 ...I cx ], where x is the number of valid data groups in the corresponding period, and its value is less than or equal to the total number of real-time three-phase current data groups in the period. The subscript letter of each element represents the data sequence number, that is, the time series of data acquisition.

[0072] S204. Based on the time series matrix, a dynamic time warping algorithm is used to obtain a dynamic warping distance between the corresponding two-phase currents as the similarity between the two-phase current curves.

[0073] Specifically, based on the time series matrix of any two phases, an m*m order Euclidean distance matrix of the corresponding two phases is constructed, where m is the number of groups of valid data in the corresponding cycle. According to the Euclidean distance matrix of the two phases, the dynamic time warping algorithm is used to solve the cumulative distance. The cumulative distance is the dynamic warping distance between the two-phase currents, that is, the similarity between the two-phase current curves. For example, taking phase A and phase B as an example, the Euclidean distance matrix of phase AB can be expressed as in, Based on the Euclidean distance matrix of the AB phase, the cumulative distance formula dis(i,j)=dis(I ai ,I bj )+min{dis(i-1,j-1),dis(i-1,j),dis(i,j-1)}, solve the cumulative distance between the AB phase currents, and finally obtain the dynamic regularization distance M[X A ,Y B ]=dis(m,m) as the similarity between the AB phase current curves, where X A and Y B is the A-phase and B-phase current sequence with a time length of m. Then, the similarity of the corresponding two-phase current curves of the AC phase and the BC phase is calculated in this way. In this way, the similarity between the two current curves in all three-phase unbalanced cycles is determined.

[0075] S205 , comparing the similarity between the current curves of every two phases in the cycle, and determining the maximum similarity phase of the cycle.

[0076] Specifically, the maximum similarity pair refers to the two phases with the greatest similarity of current curves in the corresponding cycle, which may be any one of the AB phase, the AC phase and the BC phase. The similarity of the current curves of each two phases in the cycle is compared, and the two phases with the greatest similarity are determined as the maximum similarity pair of the corresponding cycle.

[0077] S206: Determine a reference relative corresponding to the preset time period according to the number of times each relative is repeatedly determined as the maximum similar relative within the preset time period.

[0078] Specifically, the preset time period includes multiple cycles, each cycle corresponds to a maximum similarity phase, and the maximum similarity phase corresponding to a cycle may be any one of the AB phase, AC phase, and BC phase. Then, according to the maximum similarity phase corresponding to each cycle in the preset time period, the number of times each phase is repeatedly determined as the maximum similarity phase in the preset time period can be summarized. Taking the AB phase as an example, if the α of a cycle is AB =

[0079] max{α AB ,α AC ,α BC}, then the S corresponding to this period AB =1, where α AB , α AC and α BC are the similarities of the current curves of the AB phase, AC phase and BC phase of the cycle respectively; if a cycle α AB ≠max{α AB ,α AC ,α BC}, then S AB = 0. Finally, after determining the maximum similarity of all cycles within the preset time period, AB Accumulate The maximum number of times N1 that the AB phase is repeatedly determined as the same phase within the preset time period is determined, where n is the number of unbalanced cycles within the preset time period. In this way, the maximum number of times N2 and N3 that the AC phase and the BC phase are repeatedly determined as the same phase within the preset time period are determined respectively.

[0080] The phase with the most repeated determination as the maximum similar phase is determined as the reference phase corresponding to the preset time period. The number of times N1, N2 and N3 of the three phases AB, AC and BC being repeatedly determined as the maximum similar phase is compared, and the phase corresponding to the maximum number is determined as the reference phase.

[0081] Exemplarily, in the case where a preset time period includes 20 three-phase unbalanced cycles, if the number of times that AB phase, BC phase and BC phase are repeatedly determined as the maximum similar phase are 10, 7 and 3 respectively, and the number of times that AB phase is repeatedly determined as the maximum similar phase is the largest, then AB phase can be determined as the reference phase corresponding to the preset time period.

[0082] S207: The number of times the reference relative repetitions in the preset time period are determined as the maximum similarity relative is compared with the number of unbalanced cycles in the preset time period to obtain the maximum similarity ratio in the preset time period.

[0083] Specifically, the number of times the reference pair is repeatedly determined as the maximum similarity pair within the preset time period is T max , the number of unbalanced cycles in the preset time period is T, then the maximum similarity ratio in the preset time period is T max / T. Then, the maximum similarity ratio is compared with the preset ratio, and the load adjustment method applicable to the target area is determined according to the relative relationship between the two to correct the three-phase imbalance. The preset ratio is a preset value determined according to operation and maintenance experience and experimental data. For example, the preset ratio can be equal to 70%.

[0084] S208. When the maximum similarity ratio exceeds the preset ratio, determine the load adjustment applicable to the target substation.

[0085] Specifically, if the maximum similarity ratio determined in step S207 is higher than the preset ratio, it indicates that the imbalance phases of the three-phase imbalance in the preset substation are relatively concentrated, and the target substation is suitable for correcting the three-phase imbalance by load adjustment.

[0086] S209: Construct a power consumption matrix of all single-phase users in the target substation in a single cycle and its corresponding power consumption phase sequence matrix.

[0087] S210, using the power consumption matrix and the power phase sequence matrix used to express the three-phase total power consumption function of the target substation.

[0088] Specifically, in the process of constructing the function, the power consumption and power phase sequence of the single-phase users in the target area can be represented by matrices respectively. The order of the power consumption and power phase sequence in the matrix can be arranged according to the identity number of the single-phase users, forming the power consumption matrix Q = [Q1, Q2, ..., Q n ] and its corresponding power phase sequence matrix E=[e1,e2,...,e n ], where Q n represents the power consumption of the nth single-phase user in the preset time period, e n Indicates the power phase sequence of the nth single-phase user. If the power phase sequence is phase A, then its power phase sequence e=[1,0,0] T; The power phase sequence is B phase, then its power phase sequence e=[0,1,0] T ; The power phase sequence is C phase, then its power phase sequence e=[0,0,1] T Then, the target area's power consumption matrix and power consumption phase sequence matrix are used to represent the three-phase total power consumption, forming the target area's three-phase total power consumption function within the preset time period.

[0089] S211. Use an optimization algorithm to perform multi-objective optimization on the three-phase total power consumption function to determine a load adjustment strategy.

[0090] For example, according to the total power of the preset area in the preset time period and the total monthly power of each user in the area, the theoretical power required to be adjusted for each phase of the area is calculated. For the preset area, the currents of the nth collection points A, B, and C in the area are recorded as I an ,I bn , and I cn , where n = 1, 2, ... N, (N is the total number of sampling times in the preset time period) to form a current matrix Then the average currents of the three phases A, B, and C in the preset area are and The total average current of the three phases is expressed as In order to make the load of phases ABC as evenly distributed as possible, the power that needs to be adjusted for phases A, B, and C is and in, Q 总 It can be calculated based on real-time three-phase current data, voltage data, power factor data and other data within a preset time period or measured by a metering device, which will not be described in detail here.

[0091] Based on the three-phase total power consumption function shown in step S210, the three-phase total power consumption of the target area before load adjustment can be expressed as If the power phase sequence matrix of each single-phase user in the target area after load adjustment is Then the total three-phase power consumption of the target area after load adjustment can be expressed as Among them, e n | It indicates the power phase sequence of the nth single-phase user after load adjustment. The power phase sequence can be [1,0,0] according to the corresponding power phase sequence. T , [0,1,0] T or [0,0,1] T .

[0092] The first objective function represents the imbalance of three-phase power consumption. The imbalance of three-phase power consumption can be expressed as the maximum value of the difference between the theoretical adjustment power of the three phases and the actual adjustment power as γ MAX(ΔE) =MAX{γΔA , γ ΔB , γ ΔC},in,

[0093] The second objective function represents the number of adjusted users. Let the number of adjusted users be k. In the phase sequence matrix, if there is adjustment, k = 1, and if there is no adjustment, k = 0. The number of adjusted users can be expressed as

[0094]

[0095] The objectives of multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption. The overall objective function can be expressed as Vector encoding is performed on the one-way users in the preset area. The number of users of phases A, B, and C in the preset area is d, e, and f. Then the encoding matrix of the user power phase sequence can be expressed as E = [e1, e2, ..., e d ,...e d+e+f ]. Apply the multi-objective function to the optimization algorithm for calculation and solution. For example, the optimization algorithm can be a multi-objective genetic algorithm. By setting 100 times as the number of iterations of the genetic algorithm, and setting the initial population number to the number of single-phase users, the crossover probability to 0.8, and the mutation probability to 0.1, iterative calculation is performed, and the coding matrix of the adjusted power phase sequence corresponding to the optimal solution can be output. According to the comparison of the coding matrix of the power phase sequence before and after the adjustment, the load adjustment strategy can be determined.

[0096] In the three-phase unbalanced load adjustment method provided in this embodiment, a dynamic time warping algorithm is used to obtain the dynamic warping distance between the corresponding two-phase currents as the similarity between the two-phase current curves, and a multi-objective genetic algorithm is used to perform multi-objective optimization on the three-phase total power consumption function, thereby achieving accurate judgment of the applicability of the adjustment method and rapid determination of the adjustment strategy, greatly improving the efficiency and accuracy of the three-phase unbalanced adjustment, thereby reducing the impact on users.

[0097] Figure 3 The following is a schematic diagram of the structure of a three-phase unbalanced load adjustment device provided by an embodiment of the present invention. Figure 3As shown, the three-phase unbalanced load adjustment device 300 includes a data acquisition module 301, a similarity determination module 302, an applicability judgment module 303, a function construction module 304 and a strategy determination module 305. The data acquisition module 301 is used to obtain the three-phase current data of the target substation within a preset time period. The similarity determination module 302 is used to determine the similarity between each two-phase current curve in each cycle according to the three-phase current data, wherein the preset time period includes multiple cycles. The applicability judgment module 303 is used to determine whether the target substation is suitable for load adjustment according to the similarity between each two-phase current curve in each cycle in the preset time period. The function construction module 304 is used to construct the three-phase total power consumption function of the target substation when the target substation is suitable for load adjustment. The strategy determination module 305 is used to perform multi-objective optimization on the three-phase total power consumption function using an optimization algorithm to determine the load adjustment strategy, wherein the objectives of the multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption.

[0098] The three-phase unbalanced load adjustment device provided in the embodiment of the present invention can execute the three-phase unbalanced load adjustment method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0099] Figure 4 A schematic diagram of an electronic device that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0100] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0101] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0102] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a three-phase unbalanced load adjustment method.

[0103] In some embodiments, the three-phase unbalanced load adjustment method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the three-phase unbalanced load adjustment method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the three-phase unbalanced load adjustment method in any other appropriate manner (for example, by means of firmware).

[0104] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0105] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0106] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0107] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0108] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0109] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0110] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0111] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A three-phase unbalanced load adjustment method, characterized in that: include: Obtain three-phase current data of the target area within a preset time period; Determine the similarity between each two-phase current curve in each cycle according to the three-phase current data, wherein the preset time period includes a plurality of the cycles; Determining whether the target substation is suitable for load adjustment according to the similarity between the current curves of each two phases in each of the cycles in the preset time period; In the case where the target area is suitable for load adjustment, constructing a three-phase total power consumption function of the target area; The three-phase total power consumption function is optimized by a multi-objective optimization algorithm to determine a load adjustment strategy, wherein the objectives of the multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption.

2. The three-phase unbalanced load adjustment method according to claim 1, characterized in that: The step of obtaining the three-phase current data of the target substation within a preset time period includes: In each of the cycles of the preset time period, real-time three-phase current data of the target substation is collected once every unit time period; All the real-time three-phase current data are screened and processed according to the load rate and the three-phase imbalance corresponding to the real-time three-phase current data.

3. The three-phase unbalanced load adjustment method according to claim 2, characterized in that: The screening and processing of all the real-time three-phase current data in the period according to the load rate and the three-phase imbalance corresponding to the real-time three-phase current data includes: Calculating the load rate and the three-phase imbalance corresponding to the real-time three-phase current data; The real-time three-phase current data corresponding to the load rate being higher than the preset load rate and the three-phase imbalance being higher than the preset imbalance is screened out as valid data.

4. The three-phase unbalanced load adjustment method according to claim 1, characterized in that: Determining the similarity between each two-phase current curve in each cycle according to the three-phase current data includes: Based on the three-phase current data, construct a time series matrix of each two-phase current in the cycle; On the basis of the time series matrix, a dynamic time warping algorithm is used to obtain a dynamic warping distance between the corresponding two-phase currents as the similarity between the two-phase current curves.

5. The three-phase unbalanced load adjustment method according to claim 1, characterized in that: The step of judging whether the target area is suitable for load adjustment according to the similarity between the current curves of each two phases in each cycle in the preset time period includes: Comparing the similarity between each two-phase current curve in the cycle, and determining the maximum similarity phase of the cycle; Determine a reference relative value corresponding to the preset time period according to the number of times each relative value within the preset time period is repeatedly determined as the maximum similar relative value; The reference relative repetition in the preset time period is determined as the number of times of the maximum similar relative, and compared with the number of unbalanced cycles in the preset time period to obtain the maximum similarity ratio of the preset time period; When the maximum similarity ratio exceeds a preset ratio, it is determined that load adjustment is applicable to the target area.

6. The three-phase unbalanced load adjustment method according to claim 1, characterized in that: The constructing of the three-phase power consumption function of the target substation includes: Constructing a power consumption matrix of all the single-phase users in the target substation in a single cycle and a corresponding power consumption phase sequence matrix; The power consumption matrix and the power phase sequence matrix are used to express the three-phase total power consumption function of the target substation.

7. The three-phase unbalanced load adjustment method according to claim 1, characterized in that: The optimization algorithm includes a multi-objective genetic algorithm.

8. A three-phase unbalanced load adjustment device, characterized in that: include: A data acquisition module is used to acquire the three-phase current data of the target substation within a preset time period; A similarity determination module, configured to determine the similarity between each two-phase current curve in each cycle according to the three-phase current data, wherein the preset time period includes a plurality of the cycles; A suitable judgment module, used for judging whether the target substation is suitable for load adjustment according to the similarity between the current curves of each two phases in each cycle in the preset time period; A function construction module, used for constructing a three-phase total power consumption function of the target area when load adjustment is applicable to the target area; The strategy determination module is used to perform multi-objective optimization on the three-phase total power consumption function using an optimization algorithm to determine a load adjustment strategy, wherein the objectives of the multi-objective optimization include minimizing the number of adjusted users and minimizing the imbalance of three-phase power consumption.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the three-phase unbalanced load adjustment method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the three-phase unbalanced load adjustment method according to any one of claims 1 to 8 when executed.

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