A data-driven verification method for the household-transformer relationship in low-voltage power distribution areas

Abstract

The present invention discloses a method for verifying the household-transformer relationship in low-voltage power distribution areas based on data driving, comprising the following steps: Step 1, calculate the line loss rate of all power distribution areas in the same residential area according to the power sales-side settlement and power supply assessment data of the power distribution area; Step 2, determine whether the reason for the unqualified line loss rate in this residential area is an incorrect household-transformer relationship. If the unqualified line loss rate is caused by an incorrect household-transformer relationship, then execute Step 3; otherwise, reselect the residential area and execute Step 1; Step 3, establish a data-driven household-transformer relationship verification model; Step 4, solve this model and give an adjustment plan for the household-transformer relationship in the power distribution area; Step 5, adjust according to the adjustment plan in Step 4 in the power consumption acquisition system. Based on the historical data of users in the power distribution area and the power supply data of the distribution transformers in the power distribution area, the present invention uses an optimization algorithm to propose a method for verifying the household-transformer relationship based on data driving, which can effectively avoid the cumbersome work of screening households one by one in the past, so as to make the line loss rate reach a qualified level.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems and relates to a method for verifying the household-transformer relationship in low-voltage power distribution areas based on data driving. Background Art

[0002] A low-voltage power distribution area refers to the power supply range or area of a distribution transformer. The scope of line loss calculation in a low-voltage power distribution area starts from the watt-hour meter installed at the outlet of the 10 kV distribution transformer in the area and ends at each user's watt-hour meter. Within this range, all forms of power losses in all components should be included in the power grid line loss. The line loss rate is the percentage of the line loss power consumption in the power supply of the distribution transformer, which is an indicator to measure the level of line loss and an important indicator to measure the economy of the power system. At the same time, it is also a comprehensive technical indicator representing the planning and design level, production technology level, and operation and management level of the power system.

[0003] For power supply enterprises and power distribution area managers, the construction conditions of power distribution areas within their jurisdiction are uneven, and some users have behaviors such as illegal electricity use, which bring great difficulties to the lean management of power distribution areas and the reduction of line losses. At the same time, due to frequent changes in power distribution areas (such as relocation, line cutting, and capacity expansion, etc.) caused by the construction and development of low-voltage distribution networks and changes in user electricity consumption addresses, etc., it will directly lead to changes in the subordination relationship between user meters and distribution transformers in the power distribution area. If the household-transformer subordination relationship in the power distribution area is not updated in a timely manner or updated incorrectly in the user electricity consumption information collection system, it will lead to abnormal power marketing data, directly affecting the assessment and rectification of line losses in the power distribution area, and even triggering metering and bond disputes among users, resulting in losses of social resources and enterprise property.

[0004] The prior art document 1 (CN109523174B) discloses a method for verifying the household-transformer relationship in low-voltage power distribution areas based on data driving. In step 3, a verification model for the household-transformer relationship based on data driving is established. Its disadvantage is that it only considers the mutual verification between two adjacent power distribution areas, which has certain limitations. At present, projects often involve the interconnection of multiple power distribution areas. Compared with the prior art document 1, the beneficial effect of the present invention is that a general verification model for the household-transformer relationship in power distribution areas is established, which not only covers the usage scenarios in the technical document 1, but also is applicable to the verification of the household-transformer relationship among 3 or more power distribution areas, with greater applicability and popularization. Summary of the Invention

[0005] To solve the deficiencies existing in the prior art, such as abnormal line loss rates in some low-voltage power distribution areas due to chaotic household-transformer relationships and wiring errors, the purpose of the present invention is to provide a method for verifying the low-voltage household-transformer relationship based on data driving.

[0006] The present invention adopts the following technical solutions.

[0007] A data-driven verification method for household-transformer relationships in low-voltage power distribution areas, comprising the following steps:

[0008] Step 1: Calculate the line loss rate of all power distribution areas in the same residential area according to the power sales side settlement and power supply assessment data of the power distribution area;

[0009] Step 2: Determine whether the reason for the unqualified line loss rate of the residential area is an incorrect household-transformer relationship. If the judgment result is that the unqualified line loss rate is caused by an incorrect household-transformer relationship, then execute Step 3; otherwise, reselect the residential area and execute Step 1;

[0010] Step 3: Establish a data-driven household-transformer relationship verification model;

[0011] Step 4: Solve the household-transformer relationship verification model and give an adjustment plan for the household-transformer relationship in the power distribution area;

[0012] Step 5: Adjust according to the adjustment plan in Step 4 in the power consumption acquisition system.

[0013] In Step 1, the calculation method of the line loss rate of the power distribution area is:

[0014]

[0015] In Step 2, if the line loss rates of at least two power distribution areas in the residential area are not within the qualified range of 0-5%, and at least one of the line loss rates is negative, then it is determined that the reason for the unqualified line loss rate of the residential area is an incorrect household-transformer relationship.

[0016] Step 3 specifically includes:

[0017] Step 3.1: Establish a household-transformer relationship model for a system composed of multiple power distribution areas,

[0018] Step 3.2: Determine the adjustment status of users in each power distribution area,

[0019] Step 3.3: Establish a household-transformer relationship verification model.

[0020] In Step 3.1, establish a household-transformer relationship model for a system composed of four power distribution areas, which are named Power Distribution Area A, Power Distribution Area B, Power Distribution Area C, and Power Distribution Area D respectively. The total number of users in each power distribution area is I, J, M, and N respectively, and the internal users are represented as i, j, m, and n;

[0021] In Step 3.2, use a set of Boolean variables to describe the adjustment status of users in each power distribution area. X(i), Y(j), Z(m), and W(n) respectively represent the Boolean variable vectors of the adjustment status of users in Power Distribution Areas A to D, and the subscript represents the user's adjustment from one power distribution area to another.

[0022] In step 3.2, different values of the Boolean variable other than 0 or 1 can represent different adjustment states of the user, as shown in the following table.

[0023] Corresponding Table of Boolean Variable Values

[0024] Case Serial Number <![CDATA[X AB (i)]]> <![CDATA[X AC (i)]]> <![CDATA[X AD (i)]]> Status of User i Case 1 1 0 0 Adjusted to Substation Area B Case 2 0 1 0 Adjusted to Substation Area C Case 3 0 0 1 Adjusted to Substation Area D Case 4 0 0 0 Remained in Substation Area A 。

[0025] Step 3.3 specifically includes:

[0026] Step 3.3.1, establishing the equality constraints of the model, including the calculation of the daily line loss rate of the substation area and the calculation of the conversion coefficient:

[0027] The calculation formula for the daily line loss rate is:

[0028]

[0029] In the formula, δ a,t represents the line loss rate of the a-th substation area on the t-th day, where t ∈ [2, T] for the t-th day, and T is the total number of days for collecting substation area data in the system.

[0030] represents the total reading of all user electricity meters after the adjustment of the household-transformer affiliation relationship of the a-th substation area on the t-th day.

[0031] represents the reading of the power supply transformer after the adjustment of the household-transformer affiliation relationship of the a-th substation area on the t-th day; the conversion coefficient λ a,t The calculation formula is:

[0032]

[0033] Step 3.3.2, establishing the inequality constraints of the model:

[0034] Determine the qualified line loss rate constraint. The daily line loss rate of the substation area should be kept within the qualified range, that is

[0035] δ min ≤δ a,t ≤δ max

[0036] In the formula,

[0037] δ max represents the upper limit of the qualified line loss rate -1%,

[0038] δ min represents the lower limit of the qualified line loss rate 5%;

[0039] Step 3.3.3, establishing the objective function of the model:

[0040] Determine the constraints on the user status in the transformer area, that is, the status of the same user can only be retained in the original transformer area or adjusted to a single transformer area.

[0041]

[0042] In the formula,

[0043] I is the total number of users in the a-th transformer area, and for the i-th user, i ∈ [1, I].

[0044] Convert the line loss rate on the t-th day to the (t - 1)-th day. Taking the minimum fluctuation of the line loss rate after adjusting the user-transformer affiliation relationship in the transformer area as the goal, establish a data-driven user-transformer affiliation relationship verification model. The objective function is:

[0045]

[0046] In the formula,

[0047] For the t-th day, t ∈ [2, T], where T is the total number of days for collecting transformer area data in the system.

[0048] amax represents the total number of transformer areas in the system. For the a-th transformer area, a ∈ [1, amax].

[0049] The calculation formula is:

[0050]

[0051] In the formula,

[0052] P CON,a,t represents the total meter reading of all users in the a-th transformer area before adjustment.

[0053] represents the sum of the readings of the users transferred out of transformer area a.

[0054] represents the sum of the readings of the users transferred into transformer area a.

[0055] k ∈ a represents the set of transformer areas k that have user-transformer affiliation intersections or errors with transformer area a.

[0056] H ak represents the Boolean variable vector of transformer area a.

[0057] K ka represents the Boolean variable vector corresponding to transformer area k.

[0058] P a,t represents the vector of the meter readings of the users in transformer area a.

[0059] P k,t represents the vector of the meter readings of the users in transformer area k.

[0060] In step 4, for the model established in step 3, the Cplex solver in GAMS software is used for solving.

[0061] The beneficial effect of the present invention is that, compared with the prior art, based on the historical data of users and the power supply data of distribution transformers in the substation area, an optimization algorithm is used to propose a data-driven household-transformer relationship verification method. This method can give suspected users with incorrect household-transformer relationships, effectively avoiding the cumbersome work of screening households one by one, so that the line loss rate reaches a qualified level. Brief Description of the Drawings

[0062] Figure 1 It is a flowchart of a data-driven low-voltage substation area household-transformer relationship verification method of the present invention;

[0063] Figure 2 It is a multi-substation area system composed of 4 substations in a specific embodiment of the present invention;

[0064] Figure 3 It is a comparison of the daily line loss rate values of each substation area before and after the adjustment of substation area #1 in a specific embodiment of the present invention;

[0065] Figure 4 It is a comparison of the daily line loss rate values of each substation area before and after the adjustment of substation area #2 in a specific embodiment of the present invention. Detailed Embodiment

[0066] The following further describes the present application with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present application.

[0067] As Figure 1 shown, the present invention provides a data-driven low-voltage substation area household-transformer relationship verification method, which includes the following steps:

[0068] Step 1, calculate the line loss rate of all substation areas in the same residential area according to the power sales side settlement and power supply assessment data of the substation area;

[0069] Further, in step 1, calculate the line loss rate of all substation areas in the same residential area according to the power sales side settlement and power supply assessment data of the substation area:

[0070] The calculation method of the substation area line loss rate is:

[0071]

[0072]

[0073] Step 2, judge whether the reason for the unqualified line loss rate of this residential area is an incorrect household-transformer relationship;Further, in step 2, determine whether the reason for the unqualified line loss rate in this residential area is the incorrect household-transformer relationship:

[0074] Step 2.1: The characteristics of the community with incorrect household-transformer relationship are that the line loss rates of at least two transformers in the community are not within the qualified range of 0-5%, and at least one of the line loss rates is negative;

[0075] Step 2.2: According to the method in step 2.1, determine whether there is an incorrect household-transformer relationship in this residential area. That is, whether the unqualified line loss rate is caused by the incorrect household-transformer relationship. If so, execute step 3; otherwise, reselect the residential area and execute step 1;

[0076] Step 3, establish a data-driven household-transformer relationship verification model;

[0077] Further, in step 3, establish a data-driven transformer area household-transformer relationship verification model:

[0078] Step 3.1: Establish a transformer area household-transformer relationship model:

[0079] In engineering practice, most of the systems with incorrect household-transformer subordination relationships in transformer areas are systems composed of multiple transformers. To make the model more general, we take a multi-transformer area system composed of 4 transformers as an example. The four transformers are named transformer area A, transformer area B, transformer area C, and transformer area D respectively. The total number of users in each transformer area is I, J, M, and N respectively, and the internal users are represented as i, j, m, and n respectively.

[0080] Step 3.2: Determine the adjustment status of users in each transformer area:

[0081] To provide suspected incorrect archive user information for maintenance personnel to narrow down the investigation scope, we use a group of 0-1 variables (Boolean variables) to describe the adjustment status of users in each transformer area, as Figure 2 shown. Among them, X(i), Y(j), Z(m), and W(n) respectively represent the Boolean variable vectors of the adjustment status of users in transformer areas A to D. Taking X as an example, the subscript AB represents that the user is adjusted from transformer area A to transformer area B, and the subscript BA represents that the user is adjusted from transformer area B to transformer area A. Different 0 or 1 values of the Boolean variable can represent different adjustment statuses of users, as shown in Table 1.

[0082] Table 1 Corresponding table of Boolean variable values

[0083]

[0084] Step 3.3: Establish a household-transformer relationship verification model:

[0085] Step 3.3.1: Equation constraints of the model:

[0086] The equation constraints of the model include the calculation of the daily line loss rate of the substation area and the calculation of the conversion coefficient. The calculation formula of the daily line loss rate is as follows:

[0087]

[0088] In the above formula,

[0089] δ a,t represents the line loss rate of the a-th substation area on the t-th day.

[0090] W CON,a,t and W DEL,a,t are respectively the total readings of all user meters and the readings of the power supply transformer after the adjustment of the household-transformer affiliation relationship of the a-th substation area on the t-th day.

[0091] Among them, W CON,a,t can be expressed as:

[0092]

[0093] In the above formula,

[0094] P CON,a,t represents the total readings of all user meters in the a-th substation area before adjustment, that is, calculated according to the original household-transformer affiliation relationship in the power consumption acquisition system.

[0095] and respectively represent the sum of the readings of the user meters transferred out of and into the a-th substation area.

[0096] Among them,

[0097] k∈a represents the set of the k-th substation area where the household-transformer affiliation crosses or is incorrect with the a-th substation area.

[0098] H ak and K ka respectively represent the Boolean variable vectors corresponding to the a-th substation area and the k-th substation area.

[0099] P a,t and P k,t are respectively the vectors of the readings of the user meters in the a-th substation area and the k-th substation area on the t-th day.

[0100] And the calculation method of the conversion coefficient λ a,t is as follows:

[0101]

[0102] Step 3.3.2: The inequality constraints of the model:

[0103] According to the low-voltage substation area energy consumption management constraints, the daily line loss rate of the substation area should be kept within the allowable range, that is

[0104] δmin ≤δ a,t ≤δ max

[0105] wherein, δ max and δ min respectively represent the upper and lower limits of the qualified line loss rate. A preferred but non-limiting embodiment is -1% and 5%.

[0106] Meanwhile, the constraints on the user status in Table 1 can be expressed by the following formula, that is, the status of the same user can only be retained in the original area or adjusted to a single area.

[0107]

[0108] Step 3.3.3: The objective function of the model:

[0109] For a long-term qualified and stable area, since the line parameters and topology of the area have not changed, according to the relationship between the line loss rate and the power supply quantity, when the daily power supply quantities are converted to the same value, the converted line loss rates calculated using the converted power supply quantity and the total residential power consumption should remain the same.

[0110] That is, we can convert the line loss rate on the t-th day to the (t - 1)-th day according to the relationship between the power supply quantities of adjacent days of the area, and then establish a data-driven household-transformer affiliation verification model with the goal of minimizing the fluctuation of the line loss rate after the adjustment of the household-transformer affiliation relationship. Its objective function can be expressed as:

[0111]

[0112] In the above formula,

[0113] t and T respectively represent the date and the total number of days of the data used,

[0114] amax represents the total number of areas in the system.

[0115] Step 4, solve the household-transformer relationship verification model and give an adjustment plan for the household-transformer relationship in the area;

[0116] Furthermore, in Step 4, solve the model established in Step 3:

[0117] For the model established in Step 3, use the Cplex solver in the GAMS software to solve it.

[0118] Step 5, adjust according to the adjustment plan in Step 4 in the power consumption acquisition system.

[0119] Furthermore, in Step 5, adjust the household-transformer relationship in the State Grid power consumption acquisition system according to the solution result of Step 4.

[0120] The present invention will be described below by taking the residential bureau of a pair of substations as an example:

[0121] The effective days before the adjustment of the two substations were 18 days (from April 17th to May 4th of a certain year). There were a total of 8 users in the two substations, with 4 users in each substation. Due to the incorrect relationship between the household and transformer in the two substations, the line loss rate of Substation 1 was too high, while the line loss rate of Substation 2 mostly showed negative values. The daily line loss rate and the number of users of each substation before the adjustment are shown in Tables 2 and 3 below.

[0122] Table 2 Daily line loss rate of Substation 1 before adjustment

[0123]

[0124] Table 23 Daily line loss rate of Substation 2 before adjustment

[0125]

[0126]

[0127] Comparison Figure 3 and Figure 4 , after the adjustment, the line loss rates of the two substations both meet the engineering requirements, and the calculated users to be adjusted are consistent with the users actually adjusted in the project, that is, the model can meet the requirements of finding suspected users.

[0128] The beneficial effects of the present invention are that, compared with the prior art, based on the historical data of users in the substation area and the power supply data of the distribution transformer in the substation area, using an optimization algorithm, a method for verifying the relationship between households and transformers based on data-driven is proposed. This method can give suspected users with incorrect household-transformer relationships, and can effectively avoid the cumbersome work of screening households one by one, so that the line loss rate reaches a qualified level.

[0129] The applicant of the present invention has made a detailed description and explanation of the implementation examples of the present invention in combination with the accompanying drawings of the specification. However, those skilled in the art should understand that the above implementation examples are only the preferred implementation schemes of the present invention, and the detailed description is only to help readers better understand the spirit of the present invention, rather than a limitation on the protection scope of the present invention. On the contrary, any improvement or modification made based on the spirit of the present invention should fall within the protection scope of the present invention.

Claims

1. A data-driven verification method for the household-transformer relationship in low-voltage power distribution areas, characterized in that, It includes the following steps: Step 1: Calculate the line loss rate of all the substations in the same residential area according to the power sales side settlement and power supply assessment data of the substations; Step 2: Determine whether the reason for the unqualified line loss rate of the residential area is the incorrect household-substation relationship. If the judgment result is that the unqualified line loss rate is caused by the incorrect household-substation relationship, then execute Step 3; otherwise, reselect the residential area and execute Step 1; Step 3: Establish a data-driven household-substation relationship verification model including four substations. Step 3 specifically includes: Step 3.1: Establish a substation household-substation relationship model of a system composed of multiple substations, where: In Step 3.1, establish a substation household-substation relationship model of a system composed of four substations, which are respectively named Substation A, Substation B, Substation C, and Substation D. The total number of users included in each substation is I, J, M, and N respectively, and the internal users are respectively represented as i, j, m, and n; Step 3.2: Determine the adjustment status of the users in each substation, In Step 3.2, use a set of Boolean variables to describe the adjustment status of the users in each substation. X(i), Y(j), Z(m), and W(n) respectively represent the Boolean variable vectors of the user adjustment status in Substations A to D. The subscript represents that the user is adjusted from one substation to another substation. Different values of 0 or 1 of the Boolean variables can represent different adjustment statuses of the users. The corresponding values of the Boolean variables are as follows: Case 1, X AB When (i) = 1, user i is adjusted from substation area A to substation area B; Case 2, X AC When (i) = 1, user i is adjusted from substation area A to substation area C Case 3, X AD When (i) = 1, user i is adjusted from substation area A to substation area D Case 4: When all variables are 0, remain in Substation A; Step 3.3: Establish a household-substation relationship verification model, where, Step 3.3 specifically includes: Step 3.3.1: Establish the equality constraints of the model, including the calculation of the daily line loss rate of the substation and the calculation of the conversion coefficient: The calculation formula of the daily line loss rate is: where δ a,t represents the line loss rate of the a-th power distribution area on the t-th day, where t ∈ [2, T] for the t-th day, and T is the total number of days for collecting power distribution area data in the system. Denote the total reading of all user electric meters after the adjustment of the household-transformer affiliation relationship in the ath substation area on the tth day. Indicates the reading of the power supply transformer after the adjustment of the household-transformer affiliation relationship of the a-th distribution area on the t-th day; Conversion coefficient λ a,t The calculation formula is as follows: Step 3.3.2: Establish the inequality constraints of the model: Determine the qualified line loss rate constraint. The daily line loss rate of the substation should be kept within the qualified range, that is δ min ≤δ a,t ≤δ max In the formula, δ max represents the upper limit of the qualified line loss rate, which is -1%, δ min represents the lower limit of the qualified line loss rate, which is 5%; Step 3.3.3: Establish the objective function of the model: Determine the substation user status constraint, that is, the status of the same user can only be to remain in the original substation or to be adjusted to a single substation, In the formula, I is the total number of users in the a-th substation, and for the i-th user, i ∈ [1, I]; Step 4: Solve the household-substation relationship verification model and give the adjustment plan of the substation household-substation relationship; Step 5: Adjust according to the adjustment plan in Step 4 in the power consumption acquisition system.

2. A data-driven low-voltage substation household-substation relationship verification method according to claim 1, wherein: In Step 1, the calculation method of the substation line loss rate is:

3. A data-driven low-voltage substation household-substation relationship verification method according to claim 1, wherein: In Step 2, if the line loss rates of at least two substations in the residential area are not within the qualified range of 0-5%, and at least one of the line loss rates is negative, then it is judged that the reason for the unqualified line loss rate of the residential area is the incorrect household-substation relationship.

4. A data-driven low-voltage substation household-substation relationship verification method according to claim 1, wherein: The line loss rate on the t-th day is converted to the (t - 1)-th day. A data-driven household-transformer affiliation verification model is established with the goal of minimizing the fluctuation of the line loss rate after adjusting the household-transformer affiliation relationship in the transformer area. The objective function is: In the formula, For the t-th day, t ∈ [2, T], where T is the total number of days for collecting data in the transformer areas in the system. amax represents the total number of transformer areas in the system. For the a-th transformer area, a ∈ [1, amax].

5. A data-driven low-voltage transformer area household-transformer relationship verification method according to claim 1, characterized in that: The calculation formula is as follows: In the formula, P CON,a,t represents the total meter reading of all users in the a-th substation area before adjustment Indicates the sum of the user readings for staging area a, Represents the sum of the user readings transferred into substation area a, k ∈ a represents the set of transformer areas k that have household-transformer affiliation intersections or errors with transformer area a. H ak A Boolean variable vector representing the substation area a K ka Denotes the Boolean variable vector corresponding to the distribution transformer area k P a,t A vector representing the electricity meter readings of users within the transformer substation area a P k,t A vector representing the electricity meter readings of users in substation area k.

6. A data-driven low-voltage transformer area household-transformer relationship verification method according to any one of claims 1 to 5, characterized in that: In step 4, for the model established in step 3, the Cplex solver in the GAMS software is used for solving.

Images