CN110850162A - Frequency estimation method of three-phase power system based on error correlation entropy - Google Patents
Frequency estimation method of three-phase power system based on error correlation entropy Download PDFInfo
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Abstract
A frequency estimation method of a three-phase power system based on error correlation entropy comprises the following steps: A. acquiring a signal to obtain a complex voltage signal v (n) at the current moment n; B. the estimation of complex voltage signal is output by a white adaptive filter to the estimation value of complex voltage signal at the next time n +1
C. D, updating weight coefficient, calculating error related entropy β between jth time and kth time in current time windowjkAnd based on error correlation entropy βjkUpdating and calculating a standard weight coefficient h (n +1) and a conjugate weight coefficient g (n +1) of the next moment n + 1; E. calculating to obtain the frequency estimation value of the current time n of the three-phase power systemF. And (6) repeating. The method has the advantages of good impact noise resistance, high frequency estimation speed and small error.
Description
Technical Field
The present invention relates to a frequency estimation method for an electric power system, and more particularly, to a frequency estimation method for a three-phase electric power system.
Background
The frequency is one of important indexes of the power quality and is an important parameter reflecting the running state of the power system; it will vary within a small range with load variations. When the power generation amount of the generator is balanced with the load consumption, the frequency of the power system is stabilized at a specific standard value (i.e. 50 Hz). If the load connected to the power system is increased or decreased, the balance of the power system is broken, and the frequency of the power system deviates from the standard value. When the frequency of the power system deviates from the standard value, the power quality is reduced, and in severe cases, the power utilization equipment fails, even the power system is broken down, and a power failure accident occurs. Therefore, the frequency of the system needs to be monitored in time, so that measures can be taken in time to maintain the frequency at a standard value, and the power quality and the safe operation of the power system are guaranteed. Frequency monitoring of the power system is achieved through a frequency estimation algorithm.
In the frequency estimation of a three-phase power system, three-phase voltage signals are converted to a complex domain through Clark conversion; and then performing frequency estimation by using three-phase voltage information by using methods such as a phase-locked loop (PLL), an adaptive notch filter, a least square method, a minimum mean square error method, Kalman filtering and the like. The frequency estimation is made to be more robust. The augmented complex minimum mean square error method as in document 1: "Y.Xia and D.P.Mandic," Wide Linear Adaptive Frequency estimation of Unbasic Three-Phase Power Systems, "IEEE Transactions on Instrument and Measurement, vol.61, No.1, pp.74-83, Jan.2012". The estimation of the frequency value is disturbed by abnormal conditions such as harmonics, noise and unbalanced voltages. The methods are linear time sequence estimation methods, which have a good effect when the system interference noise is white gaussian noise, but when impact noise (sudden change of load and the like) occurs in a three-phase power system, the performance of the algorithm is reduced, the accuracy and reliability of the estimation value are low, and the power quality and the safe operation of the power system cannot be effectively ensured.
Disclosure of Invention
The invention aims to provide a frequency estimation method of a three-phase power system based on error correlation entropy, which has high frequency estimation speed and small error; when impact noise occurs in a three-phase power system, the method can still quickly and accurately estimate the frequency of the system; the electric energy quality and the safe operation of the power system can be more effectively ensured.
The invention achieves the technical scheme that the frequency estimation method of the three-phase power system based on the error correlation entropy comprises the following steps:
A. signal acquisition
Acquiring voltage signals of a three-phase power system, and obtaining complex voltage signals v (n) of the current moment n through Clark transformation;
B. estimation of complex voltage signals
Outputting the estimated value of the complex voltage signal at the next moment n +1 by an adaptive filter based on a wide linear model
Wherein h (n) represents the standard weight coefficient of the current time n of the filter, and the initial value is 0.99+0.15i, wherein i is an imaginary unit; g (n) represents the conjugate weight coefficient of the filter at the current time n, and the initial value is 0; v. of*(n) is the conjugate of the complex voltage signal v (n) at the current time n;
C. error calculation of complex voltage signals
The complex voltage signal v (n) at the current time n and the complex voltage signal estimated value at the current time n
Calculating the error e (n) of the complex voltage signal at the current time n,
the initial value of the error e (n) is 0.01-0.1;
D. weight coefficient update
D1 calculation of error correlation entropy
The previous L-1 time and the current time n are totally L times to form a current time window, errors e (n-L +1), e (n-L +2), … e (n-1) and e (n) of all the times in the current time window are renamed as e (n-L +1), e (n-L +2), e (n-1) and e (n) in sequence according to the time sequence in the current time window1、e2、e3…ej…ek…eLAnd then form an error vector E of the current time windown，En＝[e(n-L+1)、e(n-L+2)、…e(n-1)、e(n)]＝[e1、e2、e3…ej…ek…eL](ii) a Wherein e isj、ekRespectively the error of the jth time instant and the error of the kth time instant in the current time window, ej＝e(n-L+j)，ekE (n-L + k), j 1, 2 … … L, k 1, 2 … … L; wherein, L is the total time of the current time window, and the value of L is 15-25;
calculating the error difference value delta e between the jth moment and the kth moment in the current time windowjk，Δejk＝ej-ekFurther, the error related entropy β of the jth time and the kth time in the current time window is obtainedjk：
Wherein, sigma is the width of nucleus, and the value is 0.8-1.2;
d2 weight coefficient updating
The standard weight coefficient h (n +1) of the next time n +1 is updated and calculated,
wherein v is*(j)、v*(k) Respectively the conjugate value, v, of the complex voltage signal at the jth and kth time instants within the current time window* j＝v*(n-L+j)，v* k＝v*(n-L+k)；
The conjugate weight coefficient g (n +1) of the next time n +1 is updated and calculated,
wherein mu is the step length, and the value of mu is 0.01-0.1; v (j), v (k) are respectively the j time and the k time in the current time windowComplex voltage signal, Vj＝v(n-L+j)，Vk＝v(n-L+k)；
E. Frequency estimation
Obtaining the frequency estimation value of the current time n of the three-phase power system according to the following formula
Wherein Im (#) represents the imaginary part of the complex number, and Δ T represents the sampling interval, and the value of the Δ T is 0.0001-0.001 s;
F. and repeating the operations A to E when n is equal to n +1, namely dynamically estimating the frequency value of the three-phase power system in real time.
Compared with the prior art, the invention has the beneficial effects that:
firstly, the weight coefficient updating formula of the method of the invention applies error correlation entropy
When impact noise occurs, the error difference value delta e of each moment in the current time windowjkThe size of the liquid crystal is increased sharply,
the method only slightly increases the noise without sharp increase, so that the influence of the algorithm on impact noise is reduced, and the stability of the algorithm is improved when the impact noise occurs in the power system.
Secondly, compared with the common frequency estimation algorithm, the method only selects the error e of the current moment as the variable of the updating formula, and the weight coefficient of the method updates the adjustment item in the formula
Using the error-related entropy β of all time instants within the current time windowjkThe average value of the weight coefficient reduces the influence of errors at a few moments on the updating of the weight coefficient, and further improves the impact resistance of the algorithmThe system has good impact performance and stability and high reliability, and can quickly and accurately estimate the frequency value of the system when the power system generates impact noise.
The invention is described in further detail below with reference to the figures and the detailed description.
Drawings
FIG. 1 shows the frequency estimation of the impulse noise with 0.5% probability of occurrence added to the three-phase balanced power system, the method of this patent (labeled ACMEE in the figure) and the existing augmented complex least mean square method (labeled ACLMS in the figure)
A comparison graph of (A);
FIG. 2 shows the frequency estimation of the method of the present patent Application (ACMEE) and the method of the Augmented Complex Least Mean Square (ACLMS) when an unbalanced condition (impulse noise) occurs in a three-phase power system
A comparative graph of (a).
Detailed Description
Examples
In a specific embodiment of the present invention, a frequency estimation method for a three-phase power system based on error-related entropy includes the following steps:
A. signal acquisition
Acquiring voltage signals of a three-phase power system, and obtaining complex voltage signals v (n) of the current moment n through Clark transformation;
B. estimation of complex voltage signals
Outputting the estimated value of the complex voltage signal at the next moment n +1 by an adaptive filter based on a wide linear model
Wherein h (n) denotes the index of the filter at the current time nQuasi-weight coefficient, its initial value is 0.99+0.15i, where i is imaginary unit; g (n) represents the conjugate weight coefficient of the filter at the current time n, and the initial value is 0; v. of*(n) is the conjugate of the complex voltage signal v (n) at the current time n;
C. error calculation of complex voltage signals
The complex voltage signal v (n) at the current time n and the complex voltage signal estimated value at the current time n
Calculating the error e (n) of the complex voltage signal at the current time n,
the initial value of the error e (n) is 0.01-0.1;
D. weight coefficient update
D1 calculation of error correlation entropy
The previous L-1 time and the current time n are totally L times to form a current time window, errors e (n-L +1), e (n-L +2), … e (n-1) and e (n) of all the times in the current time window are renamed as e (n-L +1), e (n-L +2), e (n-1) and e (n) in sequence according to the time sequence in the current time window1、e2、e3…ej…ek…eLAnd then form an error vector E of the current time windown，En＝[e(n-L+1)、e(n-L+2)、…e(n-1)、e(n)]＝[e1、e2、e3…ej…ek…eL](ii) a Wherein e isj、ekRespectively the error of the jth time instant and the error of the kth time instant in the current time window, ej＝e(n-L+j)，ekE (n-L + k), j 1, 2 … … L, k 1, 2 … … L; wherein, L is the total time of the current time window, and the value of L is 15-25;
calculating the error difference value delta e between the jth moment and the kth moment in the current time windowjk，Δejk＝ej-ekFurther, the error related entropy β of the jth time and the kth time in the current time window is obtainedjk：
Wherein, sigma is the width of nucleus, and the value is 0.8-1.2;
d2 weight coefficient updating
The standard weight coefficient h (n +1) of the next time n +1 is updated and calculated,
wherein v is*(j)、v*(k) Respectively the conjugate value, v, of the complex voltage signal at the jth and kth time instants within the current time window* j＝v*(n-L+j)，v* k＝v*(n-L+k)；
The conjugate weight coefficient g (n +1) of the next time n +1 is updated and calculated,
wherein mu is the step length, and the value of mu is 0.01-0.1; v (j), V (k) are complex voltage signals of the jth time and the kth time in the current time window respectively, Vj＝v(n-L+j)，Vk＝v(n-L+k)；
E. Frequency estimation
Obtaining the frequency estimation value of the current time n of the three-phase power system according to the following formula
Wherein Im (#) represents the imaginary part of the complex number, and Δ T represents the sampling interval, and the value of the Δ T is 0.0001-0.001 s;
F. and repeating the operations A to E when n is equal to n +1, namely dynamically estimating the frequency value of the three-phase power system in real time.
The method of the present invention is verified by simulation experiments.
Simulation experiment
Simulation experiments of the method of the invention (ACMEE) and the augmented complex least mean square method (ACLMS) were performed for several typical power system conditions in a Matlab programming environment, with a sampling frequency of 2.5kHz in the simulation experiments.
Simulation experiment I
A balanced three-phase power system with the frequency of 50Hz is simulated, impact noise with the occurrence probability of 0.5 percent is added, and frequency estimation results obtained by the two methods are shown in figure 1. As can be seen from FIG. 1, under the condition of impulse noise, the Augmented Complex Least Mean Square (ACLMS) method is affected by the impulse noise, the frequency estimation value is between 47.0 Hz and 54.5Hz, the frequency estimation result has large fluctuation and large error; the frequency estimation value of the method (ACMEE) is stabilized at 49.5-50.2Hz, almost no fluctuation exists, the error is small, the influence of impact noise is small, and the frequency estimation result is accurate. Therefore, when the power system has impact noise, the method can still accurately estimate the frequency of the system.
Simulation experiment two
Simulating the situation that a three-phase power system has voltage unbalance, the 50Hz three-phase power system has voltage amplitude unbalance phenomenon when t is 0.6s, wherein B, C two-phase voltage drops by 22%, and C-phase voltage suddenly drops to 0 when t is 1.6 s. The frequency estimation results obtained by the two methods are shown in fig. 2. FIG. 2 shows that when a power system has a serious fault (single-phase ground short circuit) in 1.6s, the power system recovers to 50Hz in about 3s, and the frequency estimation result fluctuates between 47 Hz and 51.5Hz, so that the fluctuation is small and the error is small; the Augmented Complex Least Mean Square (ACLMS) method recovers to 50Hz in about 3.5s, and the frequency estimation result fluctuates between 46.5 Hz and 54.5Hz, with a large error. Therefore, when the power system has serious faults and is in an unbalanced state, the method can still quickly and accurately estimate the frequency of the system.
Claims (1)
1. A frequency estimation method of a three-phase power system based on error correlation entropy comprises the following steps:
A. signal acquisition
Acquiring voltage signals of a three-phase power system, and obtaining complex voltage signals v (n) of the current moment n through Clark transformation;
B. estimation of complex voltage signals
Outputting the estimated value of the complex voltage signal at the next moment n +1 by a white adaptive filter based on a wide linear model
Wherein h (n) represents the standard weight coefficient of the current time n of the filter, and the initial value is 0.99+0.15i, wherein i is an imaginary unit; g (n) represents the conjugate weight coefficient of the filter at the current time n, and the initial value is 0; v. of*(n) is the conjugate of the complex voltage signal v (n) at the current time n;
C. error calculation of complex voltage signals
The complex voltage signal v (n) at the current time n and the complex voltage signal estimated value at the current time n
Calculating the error e (n) of the complex voltage signal at the current time n,
the initial value of the error e (n) is 0.01-0.1;
D. weight coefficient update
D1 calculation of error correlation entropy
The previous L-1 time and the current time n are totally L times to form a current time window, errors e (n-L +1), e (n-L +2), … e (n-1) and e (n) of all the times in the current time window are renamed as e (n-L +1), e (n-L +2), e (n-1) and e (n) in sequence according to the time sequence in the current time window1、e2、e3…ej…ek…eLAnd then form an error vector E of the current time windown，En＝[e(n-L+1)、e(n-L+2)、…e(n-1)、e(n)]＝[e1、e2、e3…ej…ek…eL](ii) a Wherein e isj、ekRespectively the error of the jth time instant and the error of the kth time instant in the current time window, ej＝e(n-L+j)，ekE (n-L + k), j 1, 2 … … L, k 1, 2 … … L; wherein, L is the total time of the current time window, and the value of L is 15-25;
calculating the error difference value delta e between the jth moment and the kth moment in the current time windowjk，Δejk＝ej-ekFurther, the error related entropy β of the jth time and the kth time in the current time window is obtainedjk：
Wherein, sigma is the width of nucleus, and the value is 0.8-1.2;
d2 weight coefficient updating
The standard weight coefficient h (n +1) of the next time n +1 is updated and calculated,
wherein v is*(j)、v*(k) Respectively the conjugate value, v, of the complex voltage signal at the jth and kth time instants within the current time window* j＝v*(n-L+j)，v* k＝v*(n-L+k)；
The conjugate weight coefficient g (n +1) of the next time n +1 is updated and calculated,
wherein mu is the step length, and the value of mu is 0.01-0.1; v (j), V (k) are complex voltage signals of the jth time and the kth time in the current time window respectively, Vj＝v(n-L+j)，Vk＝v(n-L+k)；
E. Frequency estimation
From the formulaFrequency estimation value of current time n of phase power system
Wherein Im (#) represents the imaginary part of the complex number, and Δ T represents the sampling interval, and the value of the Δ T is 0.0001-0.001 s;
F. and repeating the operations A to E when n is equal to n +1, namely dynamically estimating the frequency value of the three-phase power system in real time.
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