Voltage sag prediction analysis method based on multi-dimensional multi-layer association rules

Abstract

The present application relates to the technical fields of voltage sag prediction analysis, and discloses a voltage sag prediction analysis method based on multi-dimensional multi-layer association rules, comprising the following steps: S1, inputting system structure, system impedance, line length, line impedance coefficient, line protection identification parameter and line fault probability distribution; S2, specifying sensitive load position and setting the minimum voltage allowed, calculating the critical distance of each line according to the minimum voltage amplitude; S3, when the line length is exceeded, the line is not considered, when the line length is not exceeded, whether to calculate by using the average value; S4, connecting the critical distance to the voltage sag domain by using the average value calculation. The voltage sag prediction analysis method based on multi-dimensional multi-layer association rules has high prediction efficiency and accurate results, can meet the prediction analysis of voltage sag, and is compared with the critical distance method for predicting the voltage sag area and the voltage sag frequency, so that the prediction results are more accurate.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of voltage sag prediction analysis, in particular to a voltage sag prediction analysis method based on multi-dimensional multi-layer association rules. BACKGROUND

[0002] Power quality problems include two aspects of steady-state power quality and transient power quality. With the gradual advancement of power marketization and the development of industrial automation and national economic informatization, on the one hand, non-linear loads in distribution networks pose a serious threat to the power quality of the power grid; on the other hand, the high sensitivity of power equipment such as computers to system interference puts forward requirements for high reliability, high transient constancy and high controllability of power quality. Monitoring data shows that 80% or more of existing power quality problems are caused by voltage sag, so transient power quality problems have become one of the hotspots of current domestic and foreign research.

[0003] Voltage sag refers to the sudden drop in the root mean square value of the supply voltage in a short period of time. With the technological update of power equipment, especially the large-scale application of digital automatic control technology in industrial production, higher requirements are put forward for the voltage quality of the power supply system. Voltage sag is largely caused by short-circuit faults of the line and has strong randomness, which brings great difficulties to its governance work. Therefore, a voltage sag prediction analysis method based on multi-dimensional multi-layer association rules is proposed. The method uses association rule mining. Association rule mining is an important branch of data mining. It describes the potential relationship between different data attributes in the database, finds the dependent relationship that meets the given support and confidence, and uses a specific search method to mine valuable association relationships between item sets in the data set, thereby giving a description of the association characteristics of the data set. It can help decision makers analyze the characteristics and rules of historical data and current data, and then use the critical distance method to predict the voltage sag area and the voltage sag frequency, thereby further predicting the future. SUMMARY

[0004] (I) Technical problems solved

[0005] In view of the deficiencies of the prior art, the present application provides a voltage sag prediction analysis method based on multi-dimensional multi-layer association rules, which has the advantages of effectively predicting and analyzing voltage sag, and solves the problem that voltage sag is largely caused by short-circuit faults of the line and has strong randomness, which brings great difficulties to its governance work.

[0006] (II) Technical solutions

[0007] In order to realize the above-mentioned purpose of effectively predicting and analyzing voltage sag, the present application provides the following technical scheme: a voltage sag prediction and analysis method based on multi-dimensional and multi-layer association rules, comprising the following steps:

[0008] S1, inputting system structure, system impedance, line length, line impedance coefficient, line protection identification parameter and line fault probability distribution;

[0009] S2, specifying a sensitive load position and setting the minimum voltage allowed, calculating the critical distance of each line according to the minimum voltage amplitude;

[0010] S3, when the line length is exceeded, the line is not considered, and when the line length is not exceeded, whether to use the average value for calculation;

[0011] S4, using the average value for calculation, connecting the critical distance to the voltage sag domain and calculating the total length of the line, then using the average time of line protection action to calculate the duration of voltage sag, and finally using the average fault probability of the line to obtain the frequency of voltage sag;

[0012] S5, not using the average value for calculation, calculating the duration of voltage sag according to the protection setting time of each line, then calculating the frequency of voltage sag according to the fault probability distribution of each line, and counting all the characteristic quantities of voltage sag;

[0013] S6, obtaining the final characteristic quantity of voltage sag and prediction result.

[0014] Preferably, it further comprises establishing an association rule library, then inputting the characteristic quantity, outputting the result of the association rule library, comparing with the final prediction result, taking the average value of the two, and obtaining the final prediction result.

[0015] Preferably, the association rule library comprises monitoring area, season, time period, date, voltage level, load type, result dimension, support degree and confidence degree, wherein the monitoring area corresponds to the position information of the monitoring point, and the result dimension is the pointing target of the association rule.

[0016] Preferably, it further comprises that when the power system fails, the voltage sag amplitude of the PCC (point of common coupling) point can be calculated, then compared with the given voltage, so as to judge whether it has adverse effects on the sensitive load of the PCC point.

[0017] Preferably, the critical distance calculation is that when the power supply voltage is V S =1p.u, the voltage sag amplitude of the PCC point caused by the fault is:

[0018]

[0019] wherein, Vsag is the voltage sag amplitude at the PCC point, Z F is the line impedance between the fault point and the PCC point, Z S is the system impedance between the PCC point and the power supply.

[0020] Preferably, when the voltage at the PCC point (point of common coupling) decreases to the critical voltage V, the distance between the fault point and the PCC point is the critical distance, and when the X / R value of the line impedance and the system impedance is equal, the calculation formula of the critical distance is:

[0021]

[0022] The related fault occurring within the critical distance will make the sensitivity of the PCC composite non-normal work.

[0023] Preferably, the voltage sag domain determination comprises adding all the critical distances to obtain the total critical distance in the voltage sag, and obtaining the frequency of the voltage sag by using the average fault probability of all lines.

[0024] (Three) beneficial effects

[0025] Compared with the prior art, the application provides a voltage sag prediction analysis method based on multi-dimensional multi-layer association rules, which has the following beneficial effects:

[0026] 1. The voltage sag prediction analysis method based on multi-dimensional multi-layer association rules, by inputting the system structure, system impedance, line length, line impedance coefficient, line protection identification parameter and line fault probability distribution, specifying the sensitive load position and setting the minimum voltage allowed, calculating the critical distance of each line according to the minimum voltage amplitude, when the line length is exceeded, the line is not considered, when the line length is not exceeded, whether to use the average value calculation, using the average value calculation, connecting the critical distance to the voltage sag domain, and calculating the total length of the line, then using the average time of line protection action to calculate the duration of the voltage sag, finally using the average fault probability of the line to obtain the frequency of the voltage sag, not using the average value calculation, calculating the duration of the voltage sag according to the protection setting time of each line, then calculating the frequency of the voltage sag according to the fault probability distribution of each line, and finally calculating the characteristic quantity of all voltage sags to obtain the final characteristic quantity and prediction result of the voltage sag, the prediction efficiency is high, the result is accurate, and the prediction analysis of the voltage sag can be satisfied.

[0027] 2、The voltage sag prediction analysis method based on the multi-dimensional multi-layer association rule, through the establishment of the association rule base, then input the characteristic quantity, the association rule base outputs the result, and compares with the final prediction result, takes the average value of the two, obtains the final prediction result, compares with the critical distance method prediction voltage sag area and voltage sag frequency, makes the prediction result more accurate. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 The critical distance method flow chart in the voltage sag prediction analysis method based on the multi-dimensional multi-layer association rule proposed by the application;

[0029] Figure 2 The voltage distributor model graph in the voltage sag prediction analysis method based on the multi-dimensional multi-layer association rule proposed by the application;

[0030] Figure 3 The association rule base flow chart in the voltage sag prediction analysis method based on the multi-dimensional multi-layer association rule proposed by the application;

[0031] Figure 4 The structure schematic diagram of the association rule base in the voltage sag prediction analysis method based on the multi-dimensional multi-layer association rule proposed by the application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0033] Embodiment one

[0034] Please refer to Figures 1-4 The voltage sag prediction analysis method based on the multi-dimensional multi-layer association rule in the embodiment includes the following steps:

[0035] S1, input the system structure, system impedance, line length, line impedance coefficient, line protection identification parameter and line fault probability distribution;

[0036] S2, specify the sensitive load position, and set the allowed minimum voltage, calculate the critical distance of each line according to the minimum voltage amplitude;

[0037] S3, when the line length is exceeded, the line is not considered, when the line length is not exceeded, whether to use the average value for calculation;

[0038] S4, using the average value calculation, the critical distance connection is voltage sag domain, and the total length of the line is calculated, then the average time of line protection action is used to calculate the duration of voltage sag, and finally the average fault probability of the line is used to get the frequency of voltage sag;

[0039] S5, without using average value calculation, the duration of voltage sag is calculated according to the protection setting time of each line, and then the frequency of voltage sag is calculated according to the fault probability distribution of each line, and the characteristic quantity of all voltage sags is counted;

[0040] S6, the final voltage sag characteristic quantity and prediction result are obtained, the voltage sag domain is determined, including adding all the critical distances to get the total critical distance in the voltage sag, and using the average fault probability of all lines to get the frequency of voltage sag.

[0041] Among them, it also includes establishing an association rule base, then inputting the characteristic quantity, the association rule base outputting the result, and comparing with the final prediction result, taking the average value of the two, getting the final prediction result, the association rule base including monitoring area, quarter, time period, date, voltage level, load type, result dimension, support and confidence, wherein the monitoring area corresponds to the monitoring point position information, and the result dimension is the pointing target of the association rule.

[0042] And, when the power system fails, the voltage sag amplitude of the PCC point can be calculated, and then compared with the given voltage to determine whether it has an adverse effect on a sensitive load at the PCC point.

[0043] In addition, the critical distance calculation, when the power supply voltage is V S =1p.u, then the voltage sag amplitude of the PCC point caused by the fault is:

[0044]

[0045] Among them, V sag is the voltage sag amplitude at the PCC point, Z F is the line impedance between the fault point and the PCC point, and Z S is the system impedance between the PCC point and the power supply.

[0046] Specifically, when the PCC voltage drops to the critical voltage V, the distance between the fault point and the PCC point is the critical distance, and when the X / R value of the line impedance and the system impedance is equal, the calculation formula of the critical distance is:

[0047]

[0048] The related fault within the critical distance will make the PCC sensitive composite non-normal work.

[0049] In the embodiment, the voltage sag is predicted and analyzed by the critical distance method in cooperation with the association rule base, which is high in efficiency and good in effect.

[0050] The application has the advantages that: by inputting system structure, system impedance, line length, line impedance coefficient, line protection identification parameter and line fault probability distribution, the sensitive load position is specified, the minimum voltage allowed is set, the critical distance of each line is calculated according to the minimum voltage amplitude, when the line length is exceeded, the line is not considered, when the line length is not exceeded, whether the average value is calculated, the critical distance is connected to the voltage sag area, the total length of the line is calculated, then the average time of line protection action is used to calculate the duration of voltage sag, finally the average fault probability of the line is used to obtain the frequency of voltage sag, without using the average value, the duration of voltage sag is calculated according to the protection setting time of each line, then the frequency of voltage sag is calculated according to the fault probability distribution of each line, the characteristic quantity of all voltage sags is counted, the final characteristic quantity and prediction result of voltage sag are obtained, the prediction efficiency is high, the result is accurate, and the prediction and analysis of voltage sag can be met.

[0051] In addition, by establishing the association rule base, then inputting the characteristic quantity, the association rule base outputs the result, and is compared with the final prediction result, the average value of the two is obtained, the final prediction result is obtained, and is compared with the critical distance method to predict the voltage sag area and the voltage sag frequency, so that the prediction result is more accurate.

[0052] Although the embodiments of the application have been shown and described, it is to be understood that for the purpose of the present application, the changes, modifications, replacements and variations of the embodiments can be made by those skilled in the art without departing from the principles and spirit of the application, and the scope of the application is defined by the appended claims and their equivalents.

Claims

1. A voltage sag prediction and analysis method based on multidimensional and multi-layer association rules, characterized in that, Includes the following steps: S1. Input system structure, system impedance, line length, line impedance coefficient, line protection assessment parameters, and line fault probability distribution; S2. Specify the location of the sensitive load and set its minimum allowable voltage. Calculate the critical distance for each line based on the minimum voltage amplitude. S3. If the length exceeds the line length, then this line is not considered; if the length does not exceed the line length, should the average value be used for calculation? S4. Using average value calculation, the critical distance is connected into a voltage sag domain, and the total length of the line is calculated. Then, the duration of the voltage sag is calculated using the average time of the line protection action. Finally, the frequency of the voltage sag is obtained using the average fault probability of the line. S5. Instead of using the average value, calculate the duration of voltage dips based on the protection setting time of each line, then calculate the frequency of voltage dips based on the fault probability distribution of each line, and statistically analyze the characteristic quantities of all voltage dips. S6. Obtain the characteristic quantities and prediction results of the final voltage sag; The critical distance calculation is performed when the power supply voltage is... Therefore, the voltage sag at the PCC point, i.e., the load side, caused by the fault is: in, This represents the voltage sag at point PCC. The line impedance between the fault point and the PCC point. The system impedance between point PCC and the power supply; This also includes the critical distance between the fault point and the PCC point when the PCC point voltage drops to the critical voltage V. When the line impedance and the system impedance X / R are equal, the formula for calculating the critical distance is: Related faults occurring within the critical distance will cause the PCC's sensitivity complex to malfunction.

2. The voltage sag prediction and analysis method based on multidimensional and multi-layer association rules according to claim 1, characterized in that, It also includes establishing an association rule base, then inputting feature quantities, the association rule base outputs results, and comparing them with the final prediction results, taking the average of the two to obtain the final prediction result.

3. The voltage sag prediction and analysis method based on multidimensional and multi-layer association rules according to claim 1, characterized in that, The association rule base includes monitoring area, quarter, time period, date, voltage level, load type, result dimension, support, and confidence. The monitoring area corresponds to the location information of the monitoring point, and the result dimension is the target of the association rule.

4. The voltage sag prediction and analysis method based on multidimensional and multi-layer association rules according to claim 1, characterized in that, It also includes the ability to determine whether a sensitive electrical load at the PCC point will be adversely affected by a power system fault by calculating the voltage sag at the PCC point and comparing it with the allowable given voltage.

5. The voltage sag prediction and analysis method based on multidimensional and multi-layer association rules according to claim 1, characterized in that, The voltage sag domain determination includes summing all critical distances to obtain the total critical distance in the voltage sag, and using the average fault probability of all lines to obtain the frequency of voltage sag occurrence.

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