JP2017083397A - Connection phase determination confidence level calculation program, device, and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain the confidence level of the determination result of a transformer connection phase in the absence of right-answer information.SOLUTION: The present invention involves: determining a phase to which a transformer is connected, on the basis of each of correlation values indicating the correlation of a phase current arising from electric power consumed by at least one user connected to a transformer connected to one of a plurality of phases that correspond to two combinations of a plurality of power distribution lines with each of line currents flowing in each of the plurality of power distribution lines; showing the distribution of vectors in which each of the correlation values constitute an element, and estimating a mixed distribution model having a plurality of components that correspond to each of the plurality of phases; and calculating the confidence level of the determination result of the phase to which the transformer is connected, on the basis of the mixed distribution model.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a connection phase determination reliability calculation program, a connection phase determination reliability calculation device, and a connection phase determination reliability calculation method.

  Conventionally, there has been proposed a technique for determining a connection phase of a transformer even when only information on power consumption of some consumers connected to the transformer can be used. In this technique, a phase current resulting from power consumed by at least one consumer connected to a transformer connected to one of phases corresponding to two combinations of a plurality of distribution lines is calculated. Then, a correlation coefficient between the phase current and each of the line currents flowing through each of the plurality of distribution lines is calculated, and a phase obtained by combining distribution lines other than the distribution line corresponding to the line current having the smallest correlation coefficient Is determined as the phase to which the transformer is connected.

Japanese Patent Laying-Open No. 2015-94752 Japanese Patent Laying-Open No. 2015-161607

  As an example of the conventional connection phase determination method, if the conditions on the use data side (data use period, smart meter introduction rate, etc.) are good, the connection phase can be determined with a correct answer rate of 95% or more. However, in addition to the fact that misjudgment can occur probabilistically, smart meters for measuring consumer power consumption are still in a transitional period (the introduction rate of 80% in 2020 The target is to be operated under adverse conditions for a while. Under such circumstances, in addition to the determination of the transformer connection phase, if the reliability of the determination result can be estimated, a complementary operation such as measuring the connection phase manually by limiting the transformer to a low reliability is possible. This is possible, and there are significant advantages in actual operation.

  However, in the prior art, only the determination result of the connection phase is output, and the reliability is not calculated. In addition, as a general reliability estimation method for judgment problems, a method is known in which reliability is obtained by applying logistic regression using a judgment index and correct answer information indicating whether or not it is a correct answer. ing. However, in the prior art transformer connection phase determination, since the purpose is to determine the connection phase, correct information cannot be used.

  As one aspect, an object is to obtain reliability for the determination result of the transformer connection phase under the condition where there is no correct answer information.

  In one aspect, the present invention provides a phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of a plurality of distribution lines. And each of the line currents flowing through each of the plurality of distribution lines. Then, based on each of the correlation values indicating the correlation between the phase current and each of the line currents, the phase to which the transformer is connected is determined. Further, a mixed distribution model representing a distribution of vectors having each of the correlation values as an element and having a plurality of components corresponding to each of the plurality of phases is estimated, and the transformer is connected based on the mixed distribution model The reliability of the determination result of the determined phase is calculated.

  As one aspect, there is an effect that the reliability of the determination result of the transformer connection phase can be obtained under the condition where there is no correct answer information.

It is the schematic which shows an example of a power distribution network. It is a block diagram which shows schematic structure of a connection phase determination reliability calculation apparatus. It is the schematic which expressed the power distribution system by the virtual circuit structure. It is a figure which shows distribution of a correlation coefficient vector. It is a figure for demonstrating the dimension compression by orthogonal projection. It is a figure which shows the projection to plane pi. It is a figure which shows an example of the calculated reliability. It is a block diagram which shows schematic structure of the computer which functions as a connection phase determination reliability calculation apparatus. It is a flowchart which shows an example of a connection phase determination reliability calculation process. It is a figure which shows an example of a power distribution information table. It is a figure which shows an example of a power consumption data table. It is a figure which shows an example of a line current data table. It is a flowchart which shows an example of a determination calculation process. It is a figure which shows an example of an output result.

  Hereinafter, an example of an embodiment according to the present invention will be described in detail with reference to the drawings.

<About transformer connection phase judgment problem>
The functions required of the power transmission and distribution system, which is a means of transmitting power, have changed greatly in the current trend of regulatory reform of the electric power business including the liberalization of the electric power market and the spread of renewable power. Among these, in the distribution system, dealing with distributed power sources such as photovoltaic power generation (Photovoltaics, PV), which is expected to be introduced in the future, is a major issue. As an example, it is necessary to manage the voltage so that the supply voltage of the power distribution system falls within a certain range (for example, 101 ± 6V, 202 ± 20V, etc.).

  The main problem in voltage management of the conventional distribution system was the voltage drop due to overload, but in the distributed power distribution system, a reverse power flow for selling power occurs, so the voltage rise at that time Is a big problem. Even in the current distribution system, the design and operation are premised on the prevention of voltage drop, but the problem of voltage rise is hardly assumed. In order to cope with this voltage rise problem, examination of a new voltage management system using various passive devices and active devices on power electronics has been started in various places.

  Here, when considering a new voltage management method, the problem of the pole transformer connection phase emerges. This means that in a three-phase three-wire distribution system, the transformer at the point of contact with the customer does not know which phase is connected to the high-voltage side among the three types of distribution line combinations (phases). It is a problem. The transformer connection phase is selected so that the load of multiple consumers is balanced as much as possible in order to keep the three-phase AC balanced, but the connection phase of the transformer to which each customer is connected is specifically There is almost no record and control about which one. For this reason, when considering the application of a new voltage management method, it is necessary to first consider the current state of the connection phase of the transformer.

  Normally, one transformer is installed for 10 to 20 customers, and considering the entire distribution system, the number of transformers for which the connection phase should be determined is enormous. Therefore, when the connection phase of the transformer in the entire distribution system is manually determined, a large cost and time are consumed.

  Therefore, in each of the following embodiments, an object is to determine a connection phase of a transformer even when only information on power consumption of some consumers connected to the transformer can be used. Here, the transformer connection phase determination problem assumed in each embodiment will be described in more detail.

  FIG. 1 shows an example of a power distribution network. The distribution system is a three-phase three-wire system, and there are three possibilities for the connecting phase of the pole transformer. Here, the distribution line on the high voltage side (6.6 kV) is called a-line, b-line, and c-line, and it corresponds to the combination of distribution lines that can be used as a transformer connection phase, ab phase, bc phase, and Let it be ca phase. Note that most of the actual pole transformers are single-phase, but here, the pole transformers are represented by three phases in order to express that there is a plurality of possibilities in the connection phase. In an actual power distribution system, the number of phases to which a transformer is connected is usually limited to one, and an operation is performed to balance three-phase loads by assigning any phase to each transformer.

  Several switches with built-in sensors are installed on the high voltage side of the power distribution system, and three types of line current and line voltage measurements can be obtained. The consumer is connected to the secondary side of the transformer and is supplied with a contract voltage (for example, 100V). A power meter with a communication function such as a smart meter is introduced in some of the consumers, and power consumption in the consumers is measured continuously. Information on the connection relationship between each customer and the transformer is managed by an electric power company, but information on the connection phase to which the transformer is connected is generally not recorded and managed.

  Transformer phase information has important implications for voltage management in the distribution system, but the investigation is costly and time consuming. Therefore, it is considered that the transformer connection phase is determined based on the measurement information of the sensor built-in switch and the consumer-side power meter. Hereinafter, specific conditions of this “transformer connection phase determination problem” will be described.

  The information that can be used to determine the transformer connection phase is summarized as follows.

(1) Measurement value of sensor built-in switch ・ Line current on the high voltage side of the distribution system (a-line, b-line, c-line)
・ Line voltage on the high voltage side of the power distribution system (between a-b, b-c, and c-a)
(2) Measured value of power meter with communication function ・ Consumer power consumption (only for some customers who have installed power meter with communication function)
(3) Consumer management information ・ Connection relationship between each customer and transformer (the connection phase of the transformer is unknown)

  The sensor built-in switch (1) is currently being introduced into the power distribution system, but it is realistic to install about one to several units for one feeder. A feeder is a part of a distribution system that radiates from a distribution substation. In a city area, a feeder usually includes about 1000 customers. The penetration rate of the power meter with communication function (2) is 2% or less as of February 2012, but it is considered that installation will proceed rapidly in the future. The sampling interval for measuring the amount of power with the power meter varies depending on the model of the power meter, but is, for example, 30 minutes. For (3), in addition to the connection-related information, information on the usage form of the connection phase of the transformer may be included. For example, the connection phase of the power line is usually limited to one per transformer.

  As described above, determining the transformer connection phase based on currently available information is the “transformer connection phase determination problem” which is the premise of the present embodiment.

  When trying to determine the connection relationship of a circuit such as a transformer connection phase from the electrical information of the distribution system, it is natural that the calculation is based on circuit theoretical calculation. However, the above available information is overwhelmingly lacking information for performing deterministic circuit calculations. Therefore, it is difficult to determine the transformer connection phase by circuit theoretical calculation based on available information. Therefore, as a second best measure, it may be possible to determine the transformer connection phase by using statistical correlation information of available information.

  Considering the combination of information available on the high voltage side and low voltage side (customer side) of the distribution system, it is conceivable to use power information in order to implement a correlation analysis technique. With power information, direct measurements can be obtained on both the high and low voltage sides. Assume that the power for each distribution line on the high-voltage side can be calculated, and the distribution line serving as the power supply path is uniquely determined for the transformer connection phase to which the consumer is connected. In this case, the transformer connection phase can be determined by performing a correlation analysis between the time series data of the power for each distribution line and the time series data of the power consumption of the customer.

  However, for example, as shown in FIG. 1, for a distribution system in which each pole transformer is connected to any one of the three phases in a three-phase three-wire system, correlation analysis using power information is performed. It is difficult in principle to determine a transformer connection phase based on a typical method (the reason will be described later). Therefore, in the present embodiment, the transformer connection phase is determined by correlation analysis using current information instead of power information.

<Configuration of connected phase determination reliability calculation device>
As shown in FIG. 2, the connection phase determination reliability calculation device 10 according to the present embodiment includes a consumer selection unit 12, a current value calculation unit 14, a correlation coefficient calculation unit 16, a connection phase determination unit 18, and reliability calculation. A unit 19 and an output processing unit 20 are provided. The connection phase determination unit 18 is an example of a determination unit of the present invention, and the reliability calculation unit 19 is an example of an estimation unit and a calculation unit of the present invention.

  The consumer selection unit 12 receives a transformer ID indicating a transformer for determining the connection phase as an input, and selects a power distribution section and a consumer corresponding to the transformer ID.

  Specifically, for example, a power distribution system as shown in FIG. 3 is considered. The example in FIG. 3 is a three-phase three-wire circuit, and the transformer is assumed to be a three-phase transformer virtually connected in a triangle. Most of the pole transformers in the actual power distribution system use single-phase three-wire transformers, and usually only one phase is used, but in Fig. 3, there are multiple possibilities for the connected phases. In order to handle it, the power distribution system is represented by a virtual circuit configuration. In the present embodiment, a section between two sensor built-in switches is referred to as a “distribution section”. The customer is connected to the secondary side of the transformer.

  The correspondence relationship between the distribution section and the transformer belonging to the distribution section and the correspondence relationship between the transformer and the customer connected to the transformer are stored in the distribution information storage unit 22 as distribution information. The consumer selection unit 12 refers to the distribution information stored in the distribution information storage unit 22 and selects a distribution section and a consumer corresponding to the accepted transformer ID.

  The current value calculation unit 14 reads time-series data of power consumption in the selected consumer, converts the time-series data of power consumption into time-series data of current values, and calculates the phase current resulting from the power consumption in the consumer. Calculate time series data. For example, data measured by a power meter with a communication function such as a smart meter installed in the consumer can be used as the time series data of the power consumption in the consumer. The power consumption in the consumer is measured, for example, in units of 30 minutes, and is stored in the power consumption data storage unit 24 as time series data of power consumption for each consumer.

  The correlation coefficient calculation unit 16 reads the time series data of the line current in the selected distribution section, and calculates the correlation coefficient with the time series data of the current value calculated by the current value calculation unit 14. The time series data of the line current can be obtained from the current value measured by the sensor built-in switch that defines both ends of the distribution section. In the present embodiment, as shown in FIG. 3, since a three-phase three-wire circuit is assumed, the correlation coefficient calculation unit 16 uses each line (a line, b line, and c) on the high voltage side of the distribution system. Time-series data of line current for line) is obtained. And the correlation coefficient calculation part 16 is three types between the time series data of each line current of a line, b line, and c line, and the time series data of the current value corresponding to the power consumption in a consumer. Calculate the correlation coefficient.

  Based on the three types of correlation coefficients calculated by the correlation coefficient calculation unit 16, the connection phase determination unit 18 determines which phase on the high voltage side the target transformer is connected to. Details of the determination method will be described later.

  The reliability calculation unit 19 calculates the reliability of the determination result in the connection phase determination unit 18 based on the three types of correlation coefficients calculated by the correlation coefficient calculation unit 16. Details of the calculation method will be described later.

  The output processing unit 20 performs processing for displaying the determination result by the connection phase determination unit 18 on the display device or printing it with the printing device, and outputs the result.

  Here, the principle by which the transformer connection phase can be determined based on the correlation coefficient between the line current in each line on the high voltage side of the distribution system and the phase current resulting from the power consumption in the consumer will be described.

  When power is consumed by a consumer connected to the secondary side of the transformer, a phase current also flows through the primary side of the transformer. As described above, the current flowing through each line on the high voltage side can be measured by the sensor built-in switch.

As shown in FIG. 3, a net (complex) line current I (•) _x flowing into one distribution section is defined as in the first half of the following equation (1). At this time, the relationship between each line current I (•) _x and the phase current I (•) _i ^y is expressed by the latter half of the following formula (1) from Kirchhoff's law. In addition, I (•) is represented by a symbol in which a side point (“•”) is added on a character (“I”) in a mathematical formula, and indicates a complex number.

Here, I (•) _x is x∈ {a, b, c}, and is a (complex) current that flows through the x-ray on the high voltage side. I (•) _{x_SC1} and I (•) _{x_SC2} are current values measured by the sensor built-in switches installed at both ends of the x-ray. I (·) ^y is yε {ab, bc, ca}, and is a phase current of the y-phase of the transformer. I (·) _i ^y is y∈ {ab, bc, ca}, and is a phase current of the y phase resulting from power consumption in the i-th consumer. _ny is the number of consumers connected to the y phase.

  As can be seen from the equation (1), in the circuit shown in FIG. 3, the phase current of the transformer and the line current of the distribution line are in a one-to-two relationship, and the influence of the power consumption of the customer is three distribution lines. It will extend to two of them. Even if the customer is connected to the transformer connected to any phase, one of the two will overlap, so the power information will be independent on the high voltage side and the low voltage side (customer side). It is not suitable for connection phase determination by correlation analysis.

On the other hand, the current has a combination in which the phase current and the line current are independent. For example, from equation (1), it can be seen that the phase current I (•) _i ^ab of the ab phase due to the power consumption in a certain consumer connected to the ab phase is independent of the line current I (•) _c. . Similarly, there are combinations that are also independent in the relationship between other phase currents and line currents. Therefore, if such a correlation difference can be estimated by statistical analysis, the transformer connection phase can be determined. Therefore, in the following, determination of the transformer connection phase by correlation analysis using current information will be described.

  As described above, the high-voltage side of the distribution system is configured by a three-phase three-wire system, and there is a phase difference of 2π / 3 between each phase current. Therefore, when the subsequent stage of the equation (1) is expressed using the phase current decomposed into the amplitude and the phase, the following equation (2) is obtained.

  Further, since the amplitude of the phase current may be added as a real value if it is in phase, it can be summarized as the following equation (3).

  When the amplitude of the line current of the a line is expressed by the phase current using the equations (2) and (3), the following equation (4) is obtained.

  Here, assuming that the distribution system is a symmetric three-phase alternating current, the amplitude of the line current of the a line is expressed by the following equation (5). Note that the symmetric three-phase alternating current means that the three-phase electromotive force and frequency are equal and the phase differences are all 2π / 3.

  Expression (5) is expressed by the following equation (6) by Taylor expansion of the equation and linear approximation to express the relationship between the a-line current, the ab-phase current, and the ca-phase current: can do.

Furthermore, assuming that the load impedances connected to each phase are equal balanced loads, since I ^ab = I ^ca , the following linear approximation equation (7) regarding a minute change from the equilibrium state is obtained. .

  Since the similar approximation is possible for other line currents, a minute change in the line current can be estimated by the three approximate expressions shown in the following expression (8).

In order to apply the correlation analysis to the current information, the line current time series data I _x (t) and the phase current time series data I _d ^y (t) are defined by the following equation (9-1). (9-1) In the _formula, as _I x (t) and _I ^d y (t), each of the measured values _{I x} line current '(t), and the measured value I of the phase current' _d ^y (t) The value expressed by the variation from the time average is used.

When the line current I _x ′ (t) that flows netly in each distribution section as shown in FIG. 3 is obtained from the measured value of the sensor built-in switch, it can be handled as a real number if the amplitude of the line current is in phase. Therefore, as shown in the following equation (9-2), by subtracting the measured value in the downstream sensor built-in switch (SC2) from the measured value in the upstream sensor built-in switch (SC1), the line current I _x ′ ( t) is obtained.

In addition, the phase current I ′ _d ^y (t) resulting from the power consumption in a certain consumer d connected to the y-phase of the transformer in the formula (9-1) can be calculated by using the following formula (10). It can be calculated from the power consumption measured in (1). The voltage value in this case is treated as a constant using the contract voltage. Since the current value calculated from the power consumption and the contract voltage (effective value) measured by the power meter is an effective value, in equation (10), √2 times to obtain the amplitude (maximum value) doing. The current value calculated by the equation (10) has only the meaning of the average current at the sampling interval of the power meter. However, if equivalent processing is applied to the line current, the statistical analysis is performed. There is no problem.

Here, P _d (t) is time series data of power consumption at the customer _d , V _d is a contract voltage (effective value) of the customer d, and k is a transformer transformation ratio.

At this time, the covariance σ ^y _xd and the correlation coefficient ρ ^y _xd between the time series data I _x (t) of each line current and the time series data I ^y _d (t) of the phase current are _expressed by the following equation (11-1). Can be defined as follows.

Here, σ ^y _d is the deviation of I ^y _d (t), σ _x is the deviation of I _x (t), σ ^y _d is the deviation of I ^y _d (t), and T is the time series data The number of sampling points.

There are 3 × 3 = 9 covariances and correlation coefficients defined by the equation (11-1) depending on the combination of the subscripts x and y. The specific value of these correlation coefficients depends on how the transformer connection phase, which defines the relationship between line current and phase current, changes with time in power consumption at each consumer. It depends on the setting. In the present embodiment, since I ^y _d (t) is used only for calculating the correlation coefficient, P _d (t) may be used instead of I ^y _d (t). Here, P _d (t) = P ′ _d (t) −μ (P ′ _d (t)) (μ (•) is a time average) (see equation (10)).

  In addition, when applying to an actual problem, since the connection phase of each consumer is unknown, (11-1) type | formula is described like the following (11-2) type | formula.

  Below, the value of the correlation coefficient when an appropriate assumption is made for the time series data of power consumption will be described. If the equation (8) is applied, the time series data of each line current value can be approximated by the following equation (12).

Here, it is assumed that the phase current I _i ^y (t) resulting from the power consumption in each of all the consumers including the consumer d follows a normal distribution independent of N (0, σ ₀ ² ). First, (11) and (12) from the equation, the time-series data _I x (t) of the deviation sigma _x, and customer d is the line current when connected to ab-phase _I x of each line current (t) the covariance sigma ^ab _xd between the phase current ^I _ab d (t), determined as shown in the following equation (13).

The result of the latter part of the equation (13) shows that the ab-phase phase current I _d ^ab (t) resulting from the power consumption in the consumer d correlates only with the portion of each line current caused by the own phase current. It is obtained from the situation that there is. By substituting these results into the correlation coefficient definition formula, the correlation coefficient between each line current and the phase current of the ab phase in the case where the customer d is connected to the ab phase is expressed by the following formula (14). Can be determined as shown.

  A similar calculation is possible even when the customer d is connected to another phase. In the following equation (15), approximate equations of correlation coefficients between line currents and phase currents divided according to the connection phase of the customer d are collectively described.

  As shown in the equation (15), the transformer connection phase to which the customer d is connected and the type of correlation coefficient whose value is approximately zero correspond one-to-one. Further, the correlation coefficients other than the correlation coefficient whose value is approximately 0 have values corresponding to the distribution to the connected phases of the entire consumer.

  So far, trial calculation has been carried out assuming that there is only one consumer d. However, when information on power consumption in a plurality of consumers connected to the same transformer can be used, the determination accuracy of the transformer connection phase It is possible to improve.

Specifically, the determination accuracy of the transformer connection phase can be improved by considering a virtually large consumer that takes the total power consumption of each consumer at each measurement time. For example, the time-series data of the power consumption of n _d eaves of customers is available. Further, it is assumed that the distribution of the phase current resulting from the power consumption in this virtual consumer follows a normal distribution of N (0, n _d σ ₀ ² ). In this case, the approximate expression of the correlation coefficient is rewritten as follows (16), the difference between the correlation coefficient is changed in proportion to n _d.

  The actual phase current does not always have a normal distribution as assumed above. However, even in the general case, of the three types of correlation coefficients, there must be one line type corresponding to the correlation coefficient that has a smaller value than the others, corresponding to the connection phase of the transformer. The same applies to. Paying attention to this point, the correlation coefficient between the time series data of the line current for each line on the high voltage side of the distribution system and the time series data of the phase current resulting from the power consumption in the consumer is calculated and compared. Thus, it is possible to determine the connection phase of the transformer to which the consumer is connected. Specifically

As an example of a criterion for determining a transformer connection phase with respect to a correlation coefficient of unknown connection phase: ρ _xd (xε {a, b, c}), logic such as the following equation (17) is conceivable.

_ρad = min { _ρad , _ρbd , _ρcd } → bc phase connection _ρbd = min { _ρad , _ρbd , _ρcd } → ca phase connection (17)
ρ _cd = min {ρ _ad , ρ _bd , ρ _cd } → ab phase connection

Next, the accuracy of the transformer connection phase determination problem using the correlation coefficient will be described. In a distribution system using three-phase alternating current, in order to improve power transmission efficiency, it is common to employ connections that can balance the load in three phases. Therefore, when the total number of consumers in the distribution section to be determined is N, it is assumed that the relationship n _ab = n _bc = n _ca = N / 3 holds. In this case, the change width for each line current of the correlation coefficient shown in the equation (16) is as shown in the following equation (18).

If equation (18) is used as an index, it is possible to estimate the difficulty of the determination problem according to the conditions of the data to be used. As an example, when N = 300 and n _d = 1 are substituted, a value of about Δρ to 0.071 is obtained. This value is a size that is “no correlation” without complaint in general correlation analysis, but since equation (18) is an estimate under a kind of ideal condition, it corresponds to the connected phase. It is considered that the change width of the correlation coefficient is almost equivalent to the upper limit. Since the actual change width is expected to be smaller than this, the transformer connection phase determination by this method is how to detect a very small correlation difference between current signals buried in noise. It becomes a problem to say.

  Next, determination of the connection phase and calculation of reliability for the determination result will be described.

  In this embodiment, an approach is taken in which the distribution shape of the calculation result of the correlation coefficient for a large number of transformers is estimated, and the connection phase is determined and the reliability is calculated using this result. Specifically, for each transformer, a vector having three types of correlation coefficients as elements is defined, and the probability distribution thereof is estimated using a mixed distribution model, whereby the connected phase determination with reliability is performed.

Here, a correlation coefficient vector having three types of correlation coefficients as elements is expressed by a coordinate system (ρ _ad , ρ _bd , ρ _cd ) introduced by the following equation (19). Here, e _a , e _b , and e _c are triaxial bases.

  FIG. 4 shows an example in which such vectors corresponding to a large number of transformers are drawn as a three-dimensional scatter diagram. Each point in FIG. 4 corresponds to a correlation coefficient vector of an individual transformer. In FIG. 4, in order to make the explanation easy to understand, the shading of each point is made different according to the correct answer of the transformer connection phase, but the correct answer of this transformer connection phase is unknown in an actual application situation.

  Even though the correct answer of the transformer connection phase is unknown, the collective distribution of correlation coefficient vectors is a mixed distribution divided into three parts as shown in Fig. 4 due to the physical nature of the problem of determining the transformer connection phase. It can be seen that it can be modeled. As this mixed distribution model, if a mixed normal distribution is assumed, it can be defined as the following equation (20).

Here, τ _k is a mixing ratio, μ _k is an average vector, and S _k is a variance-covariance matrix. The parameters τ _k , μ _k , and S _k (k = 1, 2, 3) of this three-dimensional mixed normal distribution model having three components are directly determined using the maximum likelihood method and the EM algorithm that are existing techniques. It is also possible. However, in the mixed distribution estimation, if the number of parameters is large, the amount of calculation increases and the stability of the estimation also decreases. Therefore, in the present embodiment, it is considered to reduce the number of parameters by reducing the three-dimensional model of Equation (20) while avoiding a decrease in connection phase determination accuracy. Therefore, a plane π having a normal vector in the (1, 1, 1) direction in the space of the correlation coefficient vector shown in FIG. 4 is considered, and all samples of the correlation coefficient vector are orthogonally projected onto the plane π. To do.

As shown in FIG. 5, when an arbitrary correlation coefficient vector ρ is decomposed into a vector ρ _h parallel to (1,1,1) and a vector ρ _v parallel to a plane π, a three-dimensional vector is obtained. A point obtained by orthogonally projecting a point corresponding to ρ onto the plane π can be expressed by ρ _v ′ which is a two-dimensional vector. By this projective transformation, the ρ _h component of the information held by the original vector ρ is lost.

Here, [rho considering the geometric meaning of the _h components, [rho _h component further ρ _ad, ρ _bd, value decomposition on the three axes of the [rho _cd is equal. The basic logic for determining the transformer connection phase based on the correlation coefficient is a comparison of the magnitudes of the three correlation coefficients as shown in equation (17). Combining these facts, [rho _h component are those that affect the same size with respect to three of the correlation coefficient, it can be seen not to influence the judgment result of the connection phase. Therefore, it is possible to realize a reduction in the amount of calculation of the mixture distribution estimation without losing information of the connected phase by dimensional compression of data by orthogonal projection onto the plane π.

In order to express the vector ρ _v ′ shown in FIG. 5 in two dimensions on the plane π, when a coordinate system (x, y) as shown in FIG. 6 is set, an orthogonal projection onto the plane π is expressed as (21 ) It can be defined by linear transformation like the formula.

  Further, when a formula of a two-dimensional mixed normal distribution obtained by projective transformation on the plane π at this time is expressed using coordinates (x, y), the following formula (22) is obtained.

  In the present embodiment, the EM algorithm used for the estimation of the mixture distribution is a kind of nonlinear optimization. The algorithm is a calculation process in which the E step for calculating the expected value of the distribution and the M step for maximizing the likelihood are sequentially repeated until a predetermined convergence determination condition is satisfied. Therefore, the amount of calculation required for estimating the distribution parameters varies greatly depending on the nature of the data used, even when the distribution model is fixed. In addition, when a mixed normal distribution having a correlation between parameters as the target of the present embodiment is estimated using the EM algorithm, the calculation process at each step becomes complicated, so the amount of calculation is discussed. It is difficult to do.

However, if the distribution is more restricted, the calculation amount of each EM step is known from the following reference, for example, and conforms to this.
References: Shotaro Akaho, “Probability of Position, Scale, and Rotation Parameters Using ECM Method”, IEICE Transactions, D-II, Information / System, II-Pattern Processing J82-D-II (12), 2240-2250, 1999-12-25
In this paper, ECM algorithm (Expectation-Conditional Maximization, a kind of generalized EM algorithm) is used for the distribution parameters when the axis of each component of mixed normal distribution is parallel to the coordinate axis (when there is no rotation parameter). Is used to estimate. The amount of calculation at each step of the ECM algorithm is estimated to be about O (dNk) (d: number of data dimensions, N: number of data points, k: number of components of mixed normal distribution, O is Landau symbol).

  In this embodiment, N is unchanged before and after dimensional compression of data, and k is the same with k = 3, but the number of dimensions of data is reduced from 3 to 2, so that one EM step is performed. The calculation amount is first reduced to about 2/3. Although it is difficult to quantitatively describe the speed of convergence due to repetition of the EM step, the number of distribution parameters to be estimated decreases from 30 to 18 with dimensional compression. Therefore, the solution search space is significantly reduced, and the number of convergence times when compared under the same convergence determination condition can be reduced.

After the projective transformation of the correlation coefficient vector to the plane π, when the distribution parameter of the equation (22) is estimated by the EM algorithm or the like, the point (x, y) corresponding to each transformer arranged on the plane π is mixed. A probability P _k (x, y) generated from the k-th component (k = 1, 2, 3) of the distribution is estimated by the following equation (23). In the example of FIG. 6, the components correspond to the ab phase, bc phase, and ca phase components in the order of k = 1, 2, and 3, respectively.

Therefore, since it is possible to estimate the probability that the transformer corresponding to the point (x, y) belongs to each of the three connected phases, it is possible to determine that the one having the highest probability is the connected phase of the transformer. . Moreover, since P _k corresponding to the determination result also has a probability that the result is a correct answer, this value can be used as the reliability (correct answer probability) of the determination result of the transformer connection phase.

  FIG. 7 shows the result of calculating the reliability (correct answer probability) of the phase determination result of the transformer connection arranged on the plane π from the estimation result of the mixed normal distribution. In FIG. 7, the reliability distribution estimated on the plane π is expressed by gray shades.

  The reliability calculation method for the connection phase determination result described above is independent of the connection phase determination logic. For example, even if the connection phase determination logic of the correlation coefficient vector is based on the conventional geometrical one or the estimation of the distribution of other determination index vectors, the same mixed distribution consisting of three components If it has, it is possible to use the above-mentioned reliability.

  The connection phase determination reliability calculation device 10 can be realized by a computer 40 shown in FIG. 8, for example. The computer 40 includes a CPU 41, a memory 42 as a temporary storage area, and a nonvolatile storage unit 43. The computer 40 also includes an input / output interface (I / F) 44 to which an input / output device 48 is connected. The computer 40 also includes a read / write (R / W) unit 45 that controls reading and writing of data with respect to the recording medium 49 and a network I / F 46 connected to a network such as the Internet. The CPU 41, the memory 42, the storage unit 43, the input / output I / F 44, the R / W unit 45, and the network I / F 46 are connected to each other via a bus 47.

  The storage unit 43 can be realized by an HDD (Hard Disk Drive), an SSD (solid state drive), a flash memory, or the like. The storage unit 43 as a storage medium stores a connection phase determination reliability calculation program 50 for causing the computer 40 to function as the connection phase determination reliability calculation device 10. The CPU 41 reads the connection phase determination reliability calculation program 50 from the storage unit 43 and expands it in the memory 42, and sequentially executes the processes of the connection phase determination reliability calculation program 50.

  The connection phase determination reliability calculation program 50 includes a customer selection process 52, a current value calculation process 54, a correlation coefficient calculation process 56, a connection phase determination process 58, a reliability calculation process 59, and an output processing process 60.

  The CPU 41 operates as the customer selection unit 12 illustrated in FIG. 2 by executing the customer selection process 52. Further, the CPU 41 operates as the current value calculation unit 14 illustrated in FIG. 2 by executing the current value calculation process 54. Further, the CPU 41 operates as the correlation coefficient calculation unit 16 illustrated in FIG. 2 by executing the correlation coefficient calculation process 56. Further, the CPU 41 operates as the connection phase determination unit 18 illustrated in FIG. 2 by executing the connection phase determination process 58. Further, the CPU 41 operates as the reliability calculation unit 19 illustrated in FIG. 2 by executing the reliability calculation process 59. Further, the CPU 41 operates as the output processing unit 20 illustrated in FIG. 2 by executing the output processing process 60. As a result, the computer 40 that has executed the connection phase determination reliability calculation program 50 functions as the connection phase determination reliability calculation device 10.

  The function realized by the connection phase determination reliability calculation program 50 can be realized by, for example, a semiconductor integrated circuit, more specifically, an ASIC (Application Specific Integrated Circuit).

<Operation of connected phase determination reliability calculation device>
Next, the operation of the connected phase determination reliability calculation device 10 according to the present embodiment will be described. When a plurality of transformer IDs indicating transformers that are connection phase determination targets are input to the connection phase determination reliability calculation device 10, the determination process illustrated in FIG. 9 is executed in the connection phase determination reliability calculation device 10.

  In step S10 of the determination process illustrated in FIG. 9, the customer selection unit 12 receives a plurality of input transformer IDs. Next, in step S12, one transformer ID is selected from the input plurality of transformer IDs.

  Next, in step S <b> 14, the customer selection unit 12 selects a power distribution section and a customer corresponding to the selected transformer ID from the power distribution information storage unit 22. Here, the distribution information storage unit 22 stores a distribution information table as shown in FIG. 10, for example. In the distribution information table of FIG. 10, for each consumer, a consumer ID indicating the consumer, a transformer ID indicating the transformer to which the consumer is connected, and a distribution section ID indicating the distribution section to which the transformer belongs, Are stored in association with each other. Here, as shown in FIG. 3, a power distribution system is assumed in which power distribution sections sandwiched between sensor-incorporated switches installed upstream and downstream of the power distribution system are connected in series. For example, a power distribution section ID indicating a power distribution section sandwiched between the sensor built-in switch (SC1) and the sensor built-in switch (SC2) is defined as “I1-2”.

  Further, the power distribution information table of FIG. 10 includes a data availability flag indicating whether or not the power consumption data of each consumer is available. For example, when a power meter such as a smart meter installed in a consumer is connected to the connection phase determination reliability calculation device 10 via a network, the power consumption data of the consumer can be used. The data availability flag is set to “present”.

  Therefore, the consumer selection unit 12 selects the customer ID and the distribution section ID associated with the transformer ID that matches the transformer ID selected in step S12. In addition, when selecting a consumer ID, a data availability flag with “present” is selected. Moreover, when there are a plurality of corresponding customer IDs, a plurality of customer IDs are acquired.

  Next, in step S <b> 16, the current value calculation unit 14 reads power consumption data corresponding to the customer ID selected in step S <b> 14 from the power consumption data storage unit 24. For example, a power consumption data table as shown in FIG. 11 is stored in the power consumption data storage unit 24. In the power consumption data table of FIG. 11, the power consumption [kWh] measured at a constant sampling time interval (30 minutes in the example of FIG. 11) by the smart meter is accumulated as time series data of power consumption for each consumer. Has been.

  When the customer ID selected in step S14 is one, the power consumption data corresponding to the customer ID may be read as it is from the power consumption data table. For example, in the example of FIG. 10 and FIG. 11, when transformer ID = T1 is selected, only consumer ID = d1 is selected. Therefore, the consumption corresponding to consumer ID = d1 is selected from the power consumption data table. Just read the power data.

  When there are a plurality of customer IDs selected in step S14, a plurality of power consumption data corresponding to the plurality of customer IDs are read. Then, the power consumption data of the virtual consumer is created by adding the power consumption amounts for each sampling time of the plurality of power consumption data.

  For example, in the example of FIGS. 10 and 11, when the transformer ID = T2 is selected, the customer IDs = d2, d3 are selected. Note that d4 is not selected because the data availability flag is “none”. And the power consumption data corresponding to consumer ID = d2 and the power consumption data corresponding to consumer ID = d3 are read from a power consumption data table. Then, a power consumption amount of “0:00” = 0.65 + 0.51 = 1.16, a power consumption amount of “0:30” = 0.62 + 0.44 = 1.06, and so on. Power consumption data is created. As a result, the power consumption data with an improved S / N ratio is obtained as compared with the case where the power consumption data corresponding to each customer ID is used as it is, and the accuracy of the correlation coefficient calculated in the subsequent processing is improved.

  Next, in step S18, the current value calculation unit 14 converts the power consumption data read in step S16 or the generated virtual consumer power consumption data into a current value using the equation (10). This current value corresponds to time-series data of phase current resulting from power consumption in the selected consumer.

  Next, in step S20, the correlation coefficient calculation unit 16 reads three types of line currents in the power distribution section indicated by the power distribution section ID selected in step S14 from the line current data storage unit 26. The line current data storage unit 26 stores, for example, a line current data table as shown in FIG. In the line current data table of FIG. 12, the net measured at a constant sampling time interval (30 minutes in the example of FIG. 12) in each of the a line, b line, and c line of the distribution section indicated by the distribution section ID. The current value [A] is accumulated as time series data of the line current. As the current value of the line current, the value calculated by the equation (9-2) can be used by using the current values measured by the sensor built-in switches arranged at both ends of the distribution section.

Next, in step S22, the correlation coefficient calculation unit 16 uses the phase current resulting from the power consumption in the consumer converted in step S18 and the line current read in step S20 (11− 2) Three types of correlation coefficients shown in the equation are calculated. Specifically, the phase current resulting from the power consumption in the consumer is defined as I ′d (t) in equation (10), and the three types of line currents are defined as I′x (t) in equation (9-2). , Xε {a, b, c}. From formula (9-1), I _d (t) and I _x (t), which are converted into fluctuations from the average value, x∈ {a, b, c} can be calculated. Substituting into the formula, correlation coefficients ρ _ad , ρ _bd , and ρ _cd are calculated.

  Next, at step S24, the customer selection unit 12 determines whether or not the processing has been completed for all the transformer IDs received at step S10. If there is an unprocessed transformer ID, the process returns to step S12, and the customer selection unit 12 selects the next transformer ID and repeats the process. On the other hand, if the processing is completed for all transformer IDs, a phase calculation process is executed in step S26.

  Here, the determination calculation process will be described with reference to FIG.

In step S262, the reliability calculation unit 19 uses the correlation coefficient vector having the correlation coefficient calculated in step S22 as an element, and a plane π having a vector symmetric about each axis corresponding to the three phases as a normal vector π Calculates the coordinates of a point orthogonally projected onto. Specifically, the reliability calculation unit 19 calculates a vector having elements of correlation coefficients (ρ _ad , ρ _bd , ρ _cd ) calculated for each transformer ID as (x, y) according to equation (21). Convert to coordinates.

  Next, in step S264, the reliability calculation unit 19 expresses an expression of a two-dimensional mixed normal distribution obtained by projective transformation on the plane π using the coordinates (x, y). The parameters are estimated using a maximum likelihood method, an EM algorithm, or the like.

Next, in step S266, the connection phase determination unit 20 uses the parameters estimated in step S264 to calculate three connection phases for each (x, y), that is, for each transformer ID, using equation (23). The probability P _k (x, y) belonging to each of the above is calculated. k = 1, 2, and 3. In the example of FIG. 6, k = 1 corresponds to the ab phase, k = 2 corresponds to the bc phase, and k = 3 corresponds to the ca phase. Then, the connection phase determination unit 20 determines the connection phase corresponding to the component k having the largest probability P _k (x, y) as the connection phase of the transformer indicated by the transformer ID corresponding to the point (x, y). . For example, if P1 _{= ab} (x, y) = 0.6, P2 _{= bc} (x, y) = 0.3, and _{P3 = ca} (x, y) = 0.1, then connect The phase determination unit 20 determines that the connection phase of the transformer indicated by the transformer ID corresponding to the point (x, y) is the ab phase.

Next, in step S268, the reliability calculation section 19, the probability calculated in step S266 _P k (x, y) maximum value, i.e., the probability corresponding to the determined component as a connection phase _P k (x , Y) is used as the reliability of the determined connection phase. And a process returns to the connection phase determination reliability calculation process shown in FIG.

  Next, in step S28, as shown in FIG. 14, for example, the output processing unit 20 adds the reliability of the determination result to the determination result of the connection phase determined for each transformer ID, and outputs the connection result. The phase determination reliability calculation process ends.

As described above, according to the connection phase determination reliability calculation device 10 according to the present embodiment, the time series data of the line current for each line on the high voltage side of the distribution system and the phase current resulting from the power consumption at the consumer. The correlation coefficient with the time series data is calculated for each transformer. Then, assuming that the distribution of each point on the plane when the three-dimensional correlation coefficient vector having three types of correlation coefficients as elements is compressed into two dimensions is a mixed distribution model having three components, Estimate the parameters of the distribution model. Then, the probability P _k (x, y) that each point is generated from the k-th component of the mixed distribution is calculated, and the connection phase is calculated from _k when P _k (x, y) is maximum. In addition to the determination, the value of P _k (x, y) is used as the reliability of the determination result. Thereby, the reliability with respect to the determination result of a transformer connection phase can be acquired under the conditions without correct information.

  Further, by compressing the three-dimensional correlation coefficient vector into two dimensions, the calculation amount of the parameter estimation of the mixed distribution can be suppressed, and the estimation stability is also improved. Further, at the time of dimensional compression, orthogonal projection is performed on a plane having a normal vector as a normal vector with respect to an axis corresponding to each of the three types of correlation coefficients. Therefore, the component deleted by dimensional compression is a component that has the same magnitude on any axis. Therefore, in the present embodiment in which the connected phase is determined by comparing the correlation coefficients, the calculation amount can be reduced by dimensional compression without reducing the connection phase determination accuracy.

In the above-described embodiment, the case where the parameters of the mixed distribution representing the distribution when the three-dimensional correlation coefficient vector is compressed into two dimensions has been described. However, from the three-dimensional distribution without performing dimensional compression. The parameters of the mixture distribution may be estimated. In this case, the parameter of the mixture distribution shown in the equation (20) is estimated. Then, using P _k (x, y) in which “g _k (x, y)” in equation (23) is replaced with “f _k (x, y)”, the determination of the connection phase and the calculation of the reliability are performed. Just do it.

  In the above description, the connection phase determination reliability calculation program 50 is stored (installed) in the storage unit 43 in advance, but is provided in a form recorded in a storage medium such as a CD-ROM or DVD-ROM. It is also possible to do.

  Regarding the above embodiment, the following additional notes are disclosed.

(Appendix 1)
On the computer,
A phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of the plurality of distribution lines, and each of the plurality of distribution lines Determining the phase to which the transformer is connected based on each of the correlation values indicating the correlation with each of the line currents flowing through
Representing a distribution of vectors having each of the correlation values as elements, and estimating a mixed distribution model having a plurality of components corresponding to each of the plurality of phases;
A connected phase determination reliability calculation program for executing a process of calculating a reliability of a determination result of a phase to which the transformer is connected based on the mixed distribution model.

(Appendix 2)
The distribution 1 is obtained by projecting a distribution of vectors having each of the correlation values as an element onto a plane having a normal vector as a normal vector with respect to an axis corresponding to each of the correlation values as the mixed distribution model. Described connection phase determination reliability calculation program.

(Appendix 3)
As the reliability, a point indicated by a vector having each of the correlation values in the mixed distribution model as an element calculates a probability generated from each of the plurality of components of the mixed distribution model. Described connection phase determination reliability calculation program.

(Appendix 4)
The connected phase determination reliability calculation program according to any one of supplementary notes 1 to 3, wherein a phase having the highest calculated reliability is determined as a phase to which the transformer is connected.

(Appendix 5)
A phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of the plurality of distribution lines, and each of the plurality of distribution lines A determination unit for determining a phase to which the transformer is connected based on each of the correlation values indicating a correlation with each of the line currents flowing through
Representing a distribution of vectors having each of the correlation values as elements, and estimating a mixed distribution model having a plurality of components corresponding to each of the plurality of phases;
Based on the mixed distribution model, a calculation unit that calculates the reliability of the determination result of the phase to which the transformer is connected;
Connection phase determination reliability calculation device including

(Appendix 6)
The calculation unit, as the mixed distribution model, projects a vector distribution having each of the correlation values as an element onto a plane having a normal vector as a normal vector with respect to an axis corresponding to each of the correlation values. The connection phase determination reliability calculation device according to appendix 5, wherein the distribution is used.

(Appendix 7)
The calculation unit calculates, as the reliability, a probability that a point indicated by a vector having each of the correlation values in the mixed distribution model as an element is generated from each of the plurality of components of the mixed distribution model. The connection phase determination reliability calculation device according to attachment 5 or attachment 6.

(Appendix 8)
The connected phase determination reliability calculation device according to any one of appendix 5 to appendix 7, wherein the determination unit determines a phase having the highest reliability calculated by the calculation unit as a phase to which the transformer is connected.

(Appendix 9)
On the computer,
A phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of the plurality of distribution lines, and each of the plurality of distribution lines Determining the phase to which the transformer is connected based on each of the correlation values indicating the correlation with each of the line currents flowing through
Representing a distribution of vectors having each of the correlation values as elements, and estimating a mixed distribution model having a plurality of components corresponding to each of the plurality of phases;
A connected phase determination reliability calculation method for executing a process of calculating a reliability of a determination result of a phase to which the transformer is connected based on the mixed distribution model.

(Appendix 10)
(Supplementary Note 9) As the mixed distribution model, a distribution obtained by projecting a vector distribution having each correlation value as an element onto a plane having a normal vector as a normal vector with respect to an axis corresponding to each correlation value is used. The connection phase determination reliability calculation method described.

(Appendix 11)
Additional points 9 or 10 for calculating the probability that the point indicated by the vector having each of the correlation values in the mixed distribution model as the reliability is generated from each of the plurality of components of the mixed distribution model The connection phase determination reliability calculation method described.

(Appendix 12)
The connection phase determination reliability calculation method according to any one of appendix 9 to appendix 11, wherein the phase having the highest calculated reliability is determined as the phase to which the transformer is connected.

(Appendix 13)
On the computer,
A phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of the plurality of distribution lines, and each of the plurality of distribution lines Determining the phase to which the transformer is connected based on each of the correlation values indicating the correlation with each of the line currents flowing through
Representing a distribution of vectors having each of the correlation values as elements, and estimating a mixed distribution model having a plurality of components corresponding to each of the plurality of phases;
A storage medium storing a connection phase determination reliability calculation program for executing a process of calculating a reliability of a determination result of a phase to which the transformer is connected based on the mixed distribution model.

DESCRIPTION OF SYMBOLS 10 Connection phase determination reliability calculation apparatus 11 Determination part 12 Consumer selection part 14 Current value calculation part 16 Correlation coefficient calculation part 18 Connection phase determination part 19 Reliability calculation part 20 Output processing part 22 Distribution information storage part 24 Power consumption data Storage unit 26 Line current data storage unit 40 Computer 41 CPU
42 Memory 43 Storage 49 Recording medium 50 Connection phase determination reliability calculation program

Claims (6)

On the computer,
A phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of the plurality of distribution lines, and each of the plurality of distribution lines Determining the phase to which the transformer is connected based on each of the correlation values indicating the correlation with each of the line currents flowing through
Representing a distribution of vectors having each of the correlation values as elements, and estimating a mixed distribution model having a plurality of components corresponding to each of the plurality of phases;
A connected phase determination reliability calculation program for executing a process of calculating a reliability of a determination result of a phase to which the transformer is connected based on the mixed distribution model.   The distribution obtained by projecting a distribution of vectors having each of the correlation values as an element onto a plane having a symmetric vector as a normal vector with respect to an axis corresponding to each of the correlation values is used as the mixed distribution model. The connection phase determination reliability calculation program according to 1.   The probability that the point which the vector which has each of the said correlation value in the said mixed distribution model as an element shows as the said reliability was produced | generated from each of these components which the said mixed distribution model has is calculated. Item 3. A connected phase determination reliability calculation program according to Item 2.   The connected phase determination reliability calculation program according to any one of claims 1 to 3, wherein a phase having the highest calculated reliability is determined as a phase to which the transformer is connected. A phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of the plurality of distribution lines, and each of the plurality of distribution lines A determination unit for determining a phase to which the transformer is connected based on each of the correlation values indicating a correlation with each of the line currents flowing through
An estimation unit that represents a distribution of vectors having each of the correlation values as an element, and that estimates a mixed distribution model having a plurality of components corresponding to each of the plurality of phases;
Based on the mixed distribution model, a calculation unit that calculates the reliability of the determination result of the phase to which the transformer is connected;
Connection phase determination reliability calculation device including On the computer,
A phase current resulting from power consumed by at least one consumer connected to a transformer connected to any of a plurality of phases corresponding to two combinations of the plurality of distribution lines, and each of the plurality of distribution lines Determining the phase to which the transformer is connected based on each of the correlation values indicating the correlation with each of the line currents flowing through
Representing a distribution of vectors having each of the correlation values as elements, and estimating a mixed distribution model having a plurality of components corresponding to each of the plurality of phases;
A connected phase determination reliability calculation method for executing a process of calculating a reliability of a determination result of a phase to which the transformer is connected based on the mixed distribution model.