JP2006217709A - Power quality evaluating system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a power quality evaluating system which can evaluate the time-series transition of the deterioration of power quality and the degree of power quality, and besides can estimate the factor of power quality deterioration. <P>SOLUTION: A power quality computing means 13 computes a plurality of power quality values which show the degree of power quality from the quantity of electricity of consumers collected by a data collecting means 12 and preserves them in a power quality computed value preserving means 14. A power quality probability density function making means 15 makes the probability density function of each power quality value from each power quality value preserved in the power quality computed value preserving means 14. A power quality evaluating means 16 evaluates the degree of power quality, using the power quality probability density function of the power quality value made by the power quality probability density function making means 15 and the power quality judgement set value being preset for judging the degree of power quality. A power quality evaluation informing means 17 informs consumers of the evaluation of the degree of the power quality obtained by the power quality evaluating means 16. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a power quality evaluation system that evaluates deterioration of power quality due to harmonics, voltage fluctuation, voltage imbalance, instantaneous voltage drop, and the like generated in a power system.

  For power supply control to the power grid, load control, which has been performed individually for power consumers, is coordinated for the entire power consumer, and the required power quality is calculated for the power consumer. Based on this, there is one that supports optimal management and operation of power consumer power distribution facilities (see, for example, Patent Document 1).

That is, in Patent Document 1, information including at least one of a system configuration diagram, a receiving voltage, a receiving facility capacity, and contract power of a power consumer receiving and distributing facility, a plurality of receiving points, and each load device Information including at least one of current and voltage in the connected bus and feeder circuit and information including at least one of the type, capacity, operating state, and presence / absence of stoppage in case of abnormality, or abnormality The damage information at the time is acquired by the management server, and the information is associated using the association information stored in the storage means. Each information and the associated information are accumulated in the database, and are accumulated in the database. Using the information, the power quality required by the power consumer is calculated by the computing means of the management server and presented to the power consumer.
JP 2002-247780 A

  However, in Patent Document 1, power quality deterioration is evaluated from the probability of occurrence, and evaluation is performed by adding a time-series transition and frequency evaluation of the degree of power quality, and further, the degree of power quality of consumers. Therefore, the cause of power quality deterioration is not estimated, and a power quality evaluation system that can provide such an evaluation result is desired.

  An object of the present invention is to provide a power quality evaluation system capable of evaluating the time series transition and frequency of the degree of power quality deterioration and the power quality and estimating the cause of power quality deterioration.

  The power quality evaluation system according to the present invention includes a data collection unit that collects the amount of electricity measured by a measurement device installed in a consumer who receives power supplied from a power system by a data transmission device, and the data collection unit Power quality calculation means for calculating a plurality of power quality values indicating the degree of power quality from the amount of electricity, power quality calculation value storage means for storing each power quality value obtained by the power quality calculation means, and the power quality Power quality probability density function creating means for creating a probability density function of each power quality value from each power quality value saved by the calculated value saving means, and power of the power quality value created by the power quality probability density function creating means Power that evaluates the degree of power quality using a quality probability density function and a preset power quality judgment value to judge the degree of power quality And quality evaluation means, characterized in that the evaluation of the degree of power quality obtained by the power quality evaluation means and a power quality evaluation notifying means for notifying the customer.

  According to the present invention, the amount of electricity measured by a measuring device installed in a consumer who receives power supply from the power system is collected, and a plurality of power quality values indicating the degree of power quality are calculated. Since the probability density function of the value is created and the power quality probability density function of the power quality value and the power quality determination setting value set in advance to determine the degree of power quality are evaluated, The deterioration of power quality can be evaluated from the probability of occurrence.

(First embodiment)
FIG. 1 is a configuration diagram of a power quality evaluation system according to the first embodiment of the present invention. The power quality evaluation system 11 is measured from a data collection means 12 that collects an electric quantity such as voltage and current measured by a measuring device installed in a consumer who is connected to the power system and receives power supply, and is measured from the power system. Power quality calculation means 13 for calculating the degree of power quality such as harmonics, voltage fluctuation, voltage imbalance, instantaneous voltage drop, etc. from the amount of power such as voltage and current, and the power quality obtained by the power quality calculation means 13 Power quality calculation value storage means 14 for storing the degree of power (hereinafter referred to as power quality value a), and a probability density function of the power quality value a is created from the power quality value a stored by the power quality calculation value storage means 14 The power quality probability density function creating means 15 and the probability density function of the power quality value a created by the power quality probability density function creating means 15 (hereinafter referred to as the power quality probability density function f). A preset value to determine the degree of power quality (hereinafter, power quality determination setting value a ₀₎ and the power quality evaluation means 16 for evaluating the degree of power quality by using the, degree of power quality It is comprised from the electric power quality evaluation notification means 17 which notifies an evaluation to a consumer.

  FIG. 2 is an explanatory diagram of a power quality evaluation index table used when the power quality calculation means 13 calculates the degree of power quality. The power quality evaluation index table describes typical items representing power quality, typical indices representing the degree of those items, and index calculation formulas. Typical items representing power quality include, for example, harmonics, voltage fluctuations, voltage imbalance, and instantaneous voltage drop. The harmonic has a general distortion rate as a typical index, and the calculation formula is expressed by the formula (1). The smaller the harmonic content, the smaller the overall distortion rate and the better the power quality. If there is no harmonic content, the total distortion will be zero.

Total distortion factor = RMS value only for harmonics ÷ RMS value (1)
The voltage fluctuation has a voltage fluctuation rate as an index, and the calculation formula is expressed by formula (2). The smaller the voltage fluctuation, the smaller the absolute value of the voltage fluctuation rate and the better the power quality. When there is no voltage fluctuation, the voltage fluctuation rate becomes zero. When the voltage fluctuation is positive, the voltage fluctuation rate is positive, and when the voltage fluctuation is negative, the voltage fluctuation rate is negative.

Voltage fluctuation rate = Voltage fluctuation (magnitude) ÷ Reference voltage (2)
Voltage unbalance has a voltage unbalance rate as an index. The calculation formula is expressed by Formula (3). The smaller the negative phase voltage, the smaller the voltage imbalance rate and the better the power quality. If there is no reverse phase voltage, the voltage fluctuation rate becomes zero.

Voltage imbalance ratio = | Reverse phase voltage | ÷ | Normal phase voltage |
Instantaneous voltage drop (also called instantaneous drop) includes a voltage drop rate and a duration of the instantaneous voltage drop as indicators. In the following description, the voltage drop rate is considered. The calculation formula is expressed by Formula (4). The smaller the amount of voltage drop, the smaller the voltage drop rate and the better the power quality. If there is no voltage drop amount, the voltage drop rate becomes zero.

Voltage drop rate = Voltage drop amount / Reference voltage (4)
FIG. 3 is a block diagram of the data collection unit 12, the power quality calculation unit 13, and the power quality calculation value storage unit 14 in the power quality evaluation system 11. Electric quantities such as voltage and current at a measuring point are input by an instrument transformer 19 such as an instrument transformer PT and an instrument current transformer CT installed in the consumer 18. Since the input power amount is an analog amount, the AD converter 20 converts the analog amount into a digital amount. The electric quantity converted into the digital quantity is stored in the electric quantity database 23 through the transmission system 22 by the transmission device 21.

The electric quantity stored in the electric quantity database 23 is read by the electric quantity reading device 24 of the power quality calculation means 13, and the total distortion rate power quality value a ₁ is obtained by the total distortion rate calculation means 25 of the power quality calculation means 13. The voltage fluctuation rate calculating means 26 calculates the power quality value a ₂ of the voltage fluctuation rate, the voltage unbalance rate calculating means 27 calculates the power quality value a ₃ of the voltage unbalance rate, and the voltage drop rate calculating means. power quality value a ₄ of the voltage drop rate is calculated at 28. The power quality value a calculated by the power quality calculation unit 13 is stored in the power quality value database 29 by the power quality calculation value storage unit 14.

FIG. 4 is an explanatory diagram showing an example of a power quality value database in the power quality calculation value storage means. In the power quality value database 29, the power quality value a _1n of the total distortion rate, the power quality value a _2n of the voltage fluctuation rate, the power quality value a _{3n of} the voltage imbalance rate, and the power quality value a of the voltage drop rate are shown in time series. An example of database of _4n is shown. The power quality value “a” is a value obtained by calculating the index shown in the power quality evaluation index table of FIG. 2 according to the formulas (1) to (4) of the read power amount.

For example, when the power quality evaluation item is a harmonic, the power quality value a is the power quality value a _1n of the total distortion rate calculated according to the equation (1). When the power quality evaluation item is voltage fluctuation, the power quality value a is the power quality value a _2n of the voltage fluctuation rate calculated according to the equation (2). Similarly, when the power quality evaluation item is voltage unbalance, the power quality value a is the power quality value a _3n of the voltage unbalance rate calculated according to Equation (3). Similarly, when the power quality evaluation item is instantaneous voltage drop, the power quality value a is the power quality value a _4n of the voltage drop rate calculated according to the equation (4).

  FIG. 5 is a block configuration diagram of the power quality probability density function creating means 15. The power quality value a stored in the power quality value database 29 is aggregated by the power quality value aggregation means 30 in the power quality probability density function creation means 15. The totaled results are output to the probability density function applying unit 31 as the power quality value totaling result Sa, and the probability density function applying unit 31 uses the power quality value totaling result Sa to calculate the power quality probability density function f (x). create.

  FIG. 6 is a graph illustrating an example of the power quality value aggregation result Sa. The power quality value a stored in the power quality value database 29 is tabulated by the power quality value tabulating unit 30. An example of the power quality value tabulation result Sa shown in FIG. 6 is obtained by tabulating the power quality value a for a period of time t from the power quality value database 29 shown in FIG.

In FIG. 6, the vertical axis represents the frequency, and the horizontal axis represents the power quality value a. As shown in the equations (1) to (4), the power quality is the best when the power quality value a is zero, and the power quality becomes worse as the power quality value a goes from zero to the plus direction or minus direction. An example of FIG. 6, power quality value a has a value in the plus or minus directions, power quality value a may have a voltage variation rate a ₂ applies. Normally, when the power quality value a is zero, that is, when the quality is the best, the frequency is large, and as the quality deteriorates, the frequency is small, and the central portion and the peripheral portion are small as shown in FIG. It has a shape. Such a distribution can be represented by a probability distribution.

  FIG. 7 is a graph showing an example in which a histogram of the power quality value aggregation result Sa is applied to a normal distribution as a probability density function. The probability density function of the normal distribution is expressed by equation (5). In equation (5), x is the power quality value a.

図８は正規分布と標準偏差σとの関係を示した説明図である。図８に示すように、標準偏差１（以下１σ）に入る確率は６８％、標準偏差２（以下２σ）に入る確率は９５％、標準偏差３（以下３σ）に入る確率は９９．７３％である。

FIG. 8 is an explanatory diagram showing the relationship between the normal distribution and the standard deviation σ. As shown in FIG. 8, the probability of entering standard deviation 1 (hereinafter 1σ) is 68%, the probability of entering standard deviation 2 (hereinafter 2σ) is 95%, and the probability of entering standard deviation 3 (hereinafter 3σ) is 99.73%. It is.

Next, the power quality evaluation unit 16 will be described. In order to determine the degree of power quality, the power quality determination set value a ₀ is used. First, the σ value is defined by equation (8).

図９は、電力品質判定設定値ａ_０に対し電力品質値ａのばらつきの方が小さい場合の電力品質判定設定値ａ_０と正規分布との関係を示す説明図である。図９に示すように、電力品質判定設定値ａ_０に対し、電力品質値ａのばらつきの方が小さい場合は電力品質判定設定値ａ_０のσ値は大きくなる。図９の場合はσ値は３σである。

Figure 9 is an explanatory diagram showing the relationship between the power quality determination setting value a ₀ and the normal distribution for better dispersion of power quality value a smaller relative power quality determination setting value a _0. As shown in FIG. 9, with respect to power quality determination set value a _0, sigma value of power quality determination setting value a ₀ if towards the variations in power quality value a is smaller increases. In the case of FIG. 9, the σ value is 3σ.

Figure 10 is an explanatory diagram showing the relationship between the power quality determination setting value a ₀ and a normal distribution if greater in variation in the power quality value a relative power quality determination setting value a _0. In the case of FIG. 10, the σ value is 1σ. Thus, it can be said that the larger the σ value, the smaller the variation of the power quality value a with respect to the power quality determination set value a ₀ , and the better the power quality. Therefore, the σ value is a scale indicating good power quality.

  FIG. 11 is a block configuration diagram of the power quality evaluation unit 16. In the power quality evaluation unit 16, first, the σ value is calculated by the σ value calculation unit 32 using the equation (8). Next, the σ value evaluation means 33 outputs the power quality evaluation value α.

  FIG. 12 is an explanatory diagram of a power quality evaluation table used for calculating the power quality evaluation value α in the power quality evaluation means 16. FIG. 12 shows a case where the power quality is evaluated based on the magnitude of the σ value. That is, the larger the σ value is, the better the power quality is. Therefore, as shown in the power quality evaluation table of FIG.

  FIG. 13 is an explanatory diagram of the power quality evaluation notification means 17. The power quality evaluation value α calculated by the power quality evaluation means 16 is notified to the customer 18 by the power quality evaluation notification means 17. The power quality evaluation notifying unit 17 includes a transmission device 21 and a transmission system 22 and transmits the power quality evaluation value α to, for example, the server 34 of the customer 18. The power quality evaluation value α transmitted to the server 34 is notified to the customer 18 by a display device 35 such as a CRT.

  According to the first embodiment, the amount of electricity measured by the measuring device installed in the consumer who receives power supplied from the power system is collected by the data collecting means 12, and a plurality of power qualities indicating the degree of power quality are shown. The power quality calculation means 13 calculates the value, the power quality probability density function creation means 15 creates a probability density function for each power quality value, and determines the power quality probability density function of the power quality value and the degree of power quality. Therefore, since the degree of power quality is evaluated using a preset power quality determination setting value, power quality deterioration can be evaluated from the occurrence probability. Therefore, it is possible to appropriately evaluate the deterioration of the power quality.

(Second Embodiment)
FIG. 14 is a configuration diagram of the power quality evaluation system 11 according to the second embodiment of the present invention. In the second embodiment, in contrast to the first embodiment, the power quality evaluation unit 16 uses a power quality probability density function f ₁ (for each power quality created by the power quality probability density function creation unit 15. The degree of power quality is comprehensively evaluated using x) to f ₄ (x) and the power quality determination set values a _{10 to} a ₄₀ .

The power quality calculation means 13 calculates a power quality by calculating a harmonic power quality value a ₁ , a voltage fluctuation power quality value a ₂ , a voltage imbalance power quality a ₃ , and an instantaneous voltage drop power quality value a _4. The value is stored in the value storage unit 14. The power quality probability density function creating means 15 includes a harmonic power quality value a ₁ , a voltage fluctuation power quality value a ₂ , a voltage imbalance power quality a ₃ , an instantaneous voltage stored in the power quality calculated value storage means 14. for power quality value _{a 4} reduction, respectively to create a power quality probability density function _f 1 ~f _4.

In the second embodiment, the power quality evaluation unit 16 uses the power quality probability density functions f _{1 to} f ₄ of each power quality and the power quality determination setting values a _{10 to} a ₄₀ to Comprehensive quality assessment. The power quality evaluation value α in the power quality evaluation means 16 is notified to the customer 18 by the power quality evaluation notification means 17 as in the first embodiment.

  The power quality evaluation method performed in the power quality evaluation means 16 includes the following.

First, by using the power quality probabilities of the individual power quality density function _f 1 ~f ₄ and power quality determination set value _a 10 _{~a 40,} power quality judgment setting values of individual power quality _a 10 _{~a 40} within Find the probability of entering.

When the probability that the power quality value a ₁ falls within the power quality determination setting value a ₁₀ is P1 (x) (−a ₁₀ ≦ x ≦ a ₁₀ ), the probability can be obtained by Expression (9).

ここで、ｆ_１（ｘ）は、電力品質Ａの確率密度関数で式（５）で与えられる。また、ａ_１０は電力品質値ａ_１の電力品質判定設定値である。

Here, f ₁ (x) is a probability density function of power quality A and is given by equation (5). _{Also, a 10} is the power quality judgment setting value of power quality value _{a 1.}

Similarly, the power quality value a ₂ of voltage fluctuation, the power quality a ₃ of voltage imbalance, and the power quality value a ₄ of instantaneous voltage drop are within the respective power quality determination set values a _{20 to} a ₄₀ . P2 (x), P3 (x), and P3 (x), P3 (x), and P4 (x), respectively, as in P1 (x) of power quality a ₁ ), P4 (x).

The harmonic power quality value a ₁ , the voltage fluctuation power quality value a ₂ , the voltage imbalance power quality a ₃ , and the instantaneous voltage drop power quality value a ₄ , all of which are power quality determination set values a ₁₀ to If the probability of entering within a ₄₀ is P (x), the probability P (x) is expressed by equation (10).

P (x) = P1 (x) × P2 (x) × P3 (x) × P4 (x) (10)
Further, any one of the harmonic power quality value a ₁ , the voltage fluctuation power quality value a ₂ , the voltage imbalance power quality a ₃ , and the instantaneous voltage drop power quality value a _{4 is} determined. Assuming that the probability of deviating from the set values a _{10 to} a ₄₀ is Pnot (x), the probability Pnot (x) is expressed by Expression (11).

Pnot (x) = 1−P (x)
= 1−P1 (x) × P2 (x) × P3 (x) × P3 (x) (11)
Since the power quality is better as Pnot (x) is smaller and P (x) is larger, the power quality evaluation value α is shown in the table of FIG. FIG. 15 is an explanatory diagram of a power quality evaluation table used for calculation of the power quality evaluation value α in the power quality evaluation unit 16 in the second embodiment. FIG. 15 shows an example of the relationship between the magnitude of P (x) and the power quality evaluation value α. The larger the P (x), the better the power quality. As shown in the table of FIG. According to the size of (x), the evaluation is made in five stages from the one with the best power quality. FIG. 16 is a reference diagram showing the relationship between P (x) and standard deviation σ.

  According to the second embodiment, the power quality evaluation unit 16 comprehensively uses the power quality probability density function and the power quality determination setting value for each power quality created by the power quality probability density function creation unit 15. Therefore, the power quality can be judged more accurately because the degree of power quality is evaluated.

(Third embodiment)
FIG. 17 is a configuration diagram of the power quality evaluation system 11 according to the third embodiment of the present invention. In the third embodiment, a time series evaluation unit 36 for evaluating the time series transition and frequency of the degree of power quality evaluated by the power quality evaluation unit 16 is added to the first embodiment. The power quality evaluation notifying means 17 notifies the customer of the time series transition and frequency of the degree of power quality evaluated by the time series evaluating means 36.

  The time series evaluation unit 36 evaluates the time series transition and frequency of the power quality evaluation value α representing the degree of power quality evaluated by the power quality evaluation unit 16. FIG. 18 is a change transition diagram showing an example in which a change in the degree of power quality in one week is expressed by a σ value, and FIG. 19 is a change transition diagram showing an example of a change in the operation rate of a customer for one week. Comparing FIG. 18 and FIG. 19, it can be seen that the σ value is small when the operation rate is large, and the σ value is large when the operation rate is small. FIG. 20 is a correlation diagram showing the relationship between the σ value and the operating rate. FIG. 20 shows that there is a negative correlation between the σ value and the operating rate.

  According to the third embodiment, the time series evaluation means 36 evaluates the time series transition and frequency of the degree of power quality, so the cause of the power quality deterioration factor can be estimated.

(Fourth embodiment)
FIG. 21 is a configuration diagram of the power quality evaluation system 11 according to the fourth embodiment of the present invention. The fourth embodiment is different from the third embodiment in that the power quality for estimating the factor of power quality deterioration based on the time series transition and frequency of the degree of power quality evaluated by the time series evaluation means 36. The deterioration factor estimation means 37 is additionally provided, and the power quality evaluation notification means 17 notifies the consumer of the factor of the power quality deterioration estimated by the power quality deterioration factor estimation means 37.

  The power quality deterioration factor estimation means 37 estimates the power quality deterioration factor based on the time series transition and frequency of the power quality degree evaluated by the time series evaluation means 36. FIG. 22 is a change transition diagram showing an example in which a change in the degree of power quality in one week of a consumer A is expressed by a σ value. FIG. 23 is a change transition diagram showing an example in which a change in the degree of power quality for a certain customer B in one week is represented by a σ value. The power quality deterioration factor estimating means 37 inputs the time series transition and frequency of the degree of power quality shown in FIG. 22 and FIG. 23 evaluated by the time series evaluation means 36, and compares these to compare the power quality deterioration. Estimate the factors. For example, it can be seen from the change trends in FIGS. 22 and 23 that there is a likely correlation between customer A and customer B.

  FIG. 24 shows an example of the correlation degree of σ value for one week between each customer when the target customers are customer A, customer B, customer C, customer D, and customer E. FIG. From the degree of correlation shown in FIG. 24, it can be seen that the degree of correlation among customer A, customer B, and customer C is close to 1, but the other degree of correlation is close to 0. From these, it can be seen that although there is a common deterioration in power quality of customer A, customer B, and customer C, there is nothing else.

  FIG. 25 shows a weekly σ value of a customer A, customer B, customer C, customer D, customer E, and a week of a certain adjacent factory F, factory G, factory H, factory I, factory J. It is an example of the correlation diagram showing the correlation degree of the operation rate. From the degree of correlation in FIG. 25, it can be seen that consumer A, consumer B, consumer C, and factory F have a weak negative correlation of −0.6 to −0.7. It can be seen that there is a strong negative correlation close to 1 between the customer B, the customer C, and the factory G. From these, it can be seen that the main factor of the deterioration in power quality of the customer A, the customer B, and the customer C is the factory G, and the factory F has some influence. The estimation result of the cause of the power quality deterioration is notified to each consumer by the power quality evaluation notification means 17.

  According to the fourth embodiment, the time series transition and frequency of the degree of power quality are evaluated, and the factor of power quality deterioration is estimated by investigating the correlation between the operating rates of a plurality of customers and factories. be able to.

The block diagram of the electric power quality evaluation system concerning the 1st Embodiment of this invention concerning the 1st Embodiment of this invention. Explanatory drawing of the electric power quality evaluation index table | surface used when calculating the grade of electric power quality by the electric power quality calculation means in the 1st Embodiment of this invention. 1 is a block diagram of data collection means, power quality calculation means, and power quality calculation value storage means in the power quality evaluation system according to the first embodiment of the present invention. Explanatory drawing which shows an example of the power quality value database in the 1st Embodiment of this invention. The block block diagram of the power quality probability density function preparation means in the 1st Embodiment of this invention. It is a graph which shows an example of the power quality value total result of the power quality value totaled by the power quality probability density function creation means in the 1st embodiment of the present invention. It is a graph which shows an example which applied the histogram of the power quality value total result of the power quality value totaled by the power quality probability density function creation means in the 1st embodiment of the present invention to a normal distribution as a probability density function. Explanatory drawing which showed the relationship between normal distribution and standard deviation. Explanatory drawing which shows the relationship between the power quality determination setting value and normal distribution in case the variation in power quality value is smaller than the power quality determination setting value. Explanatory drawing which shows the relationship between the power quality determination setting value and normal distribution in case the variation of the power quality value a is larger than the power quality determination setting value. The block block diagram of the electric power quality evaluation means in the 1st Embodiment of this invention. Explanatory drawing of the electric power quality evaluation table | surface used for calculation of an electric power quality evaluation value in the electric power quality evaluation means in the 1st Embodiment of this invention. Explanatory drawing of the power quality evaluation notification means in the 1st Embodiment of this invention. The block diagram of the electric power quality evaluation system concerning the 2nd Embodiment of this invention. Explanatory drawing of the power quality evaluation table | surface used for calculation of the power quality evaluation value in the power quality evaluation means in the 2nd Embodiment of this invention. The reference diagram which shows the relationship between P (x) and the standard deviation (sigma) in the 2nd Embodiment of this invention. The block diagram of the electric power quality evaluation system concerning the 3rd Embodiment of this invention. An example in which a change in the degree of power quality for one week is expressed by a σ value as an example when the time series evaluation means in the third embodiment of the present invention evaluates the time series transition and frequency of the degree of power quality. The change transition diagram shown. A change transition diagram showing an example of a change in the operation rate of one week of a consumer as an example when performing a time series transition and a frequency evaluation of the degree of power quality by the time series evaluation unit in the third embodiment of the present invention . FIG. 20 is a correlation diagram showing the relationship between the σ value of FIG. 18 and the availability of FIG. The block diagram of the electric power quality evaluation system concerning the 4th Embodiment of this invention. As an example of estimating the power quality deterioration factor from the power quality level by the power quality deterioration factor estimation unit according to the fourth embodiment of the present invention, the change in the power quality level of the customer A for one week is represented by σ. The change transition diagram which shows an example represented with the value. As an example when estimating the factor of power quality deterioration from the degree of power quality by the power quality deterioration factor estimating means in the fourth embodiment of the present invention, the degree of power quality for one week of customer B is represented by σ value. This is an example. As an example when estimating the factor of power quality deterioration from the degree of power quality by the power quality deterioration factor estimating means in the fourth embodiment of the present invention, the target customers are customer A, customer B, The correlation diagram of an example showing the correlation degree of the (sigma) value of one week between each consumer at the time of being the consumer C, the consumer D, and the consumer E. As an example when estimating the factor of power quality deterioration from the degree of power quality by the power quality deterioration factor estimating means in the fourth embodiment of the present invention, customer A, customer B, customer C, customer D The correlation diagram of an example showing the correlation degree of the weekly sigma value of the customer E and the operation rate of the adjacent factory F, the factory G, the factory H, the factory I, and the factory J for one week.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 ... Electric power quality evaluation system, 12 ... Data collection means, 13 ... Electric power quality calculation means, 14 ... Electric power quality calculation value storage means, 15 ... Electric power quality probability density function creation means, 16 ... Electric power quality evaluation means, 17 ... Electric power quality Evaluation notifying means, 18 ... customer, 19 ... instrument transformer, 20 ... AD converter, 21 ... transmission device, 22 ... transmission system, 23 ... electric quantity database, 24 ... electric quantity reading device, 25 ... total distortion Calculation means 26 ... Voltage fluctuation rate calculation means 27 ... Voltage imbalance rate calculation means 28 ... Voltage drop rate calculation means 29 ... Power quality value database 30 ... Power quality value aggregation means 31 ... Probability density function application means 32 ... σ value calculating means, 33 ... σ value evaluating means, 34 ... server, 35 ... display device, 36 ... time series evaluating means, 37 ... power quality deterioration factor estimating means

Claims (4)

Data collection means for collecting the amount of electricity measured by a measurement device installed in a consumer who receives power supply from the power system by a data transmission device;
Power quality calculation means for calculating a plurality of power quality values indicating the degree of power quality from the amount of electricity collected by the data collection means;
Power quality calculation value storage means for storing each power quality value obtained by the power quality calculation means;
A power quality probability density function creating means for creating a probability density function of each power quality value from each power quality value stored by the power quality calculated value storing means;
Evaluating the degree of power quality using the power quality probability density function of the power quality value created by the power quality probability density function creating means and the power quality judgment setting value preset to judge the degree of power quality Power quality evaluation means to
An electric power quality evaluation system comprising: an electric power quality evaluation notification means for notifying the consumer of an evaluation of the degree of electric power quality obtained by the electric power quality evaluation means.   The power quality evaluation means comprehensively evaluates the degree of power quality using the power quality probability density function and the power quality determination setting value for each power quality created by the power quality probability density function creation means. The power quality evaluation system according to claim 1.   Time series evaluation means for evaluating the time series transition and frequency of the degree of power quality evaluated by the power quality evaluation means, and the power quality evaluation notification means indicates the degree of power quality evaluated by the time series evaluation means. The power quality evaluation system according to claim 1 or 2, wherein a time series transition and frequency are notified to the consumer.   A power quality deterioration factor estimating means for estimating a factor of power quality deterioration based on a time series transition and frequency of the degree of power quality evaluated by the time series evaluation means, and the power quality evaluation notifying means includes the power quality deterioration notifying means. 4. The power quality evaluation system according to claim 3, wherein a factor of power quality deterioration estimated by the factor estimating means is notified to the consumer.

Images