1. A method for checking steady-state and dynamic electrical quantity data of a regional power grid is characterized by comprising the following steps:

carrying out discrete sampling on a steady-state signal of the regional power grid at a first sampling frequency to obtain a steady-state data sequence consisting of k steady-state electrical quantity data; discrete sampling is carried out on the dynamic signal of the regional power grid at a second sampling frequency, and a dynamic data sequence consisting of k dynamic electrical quantity data is obtained;

performing difference processing on the ith steady-state electrical quantity data in the steady-state data sequence and the ith dynamic electrical quantity data in the dynamic data sequence to obtain a difference value data sequence consisting of k difference value data;

normalizing the steady-state data sequence, the dynamic data sequence and the difference data sequence to obtain a corresponding steady-state sequence, a corresponding dynamic sequence and a corresponding difference sequence;

performing feature extraction processing on the steady-state sequence, the dynamic sequence and the difference sequence to obtain a corresponding steady-state feature matrix, a corresponding dynamic feature matrix and a corresponding difference feature matrix; calculating the characteristic values of the steady-state characteristic matrix, the dynamic characteristic matrix and the difference characteristic matrix to obtain a corresponding steady-state characteristic sequence, a corresponding dynamic characteristic sequence and a corresponding difference characteristic sequence which are formed by k characteristic values;

performing difference processing on all any two adjacent characteristic values in the difference characteristic sequence to obtain absolute values of k-1 characteristic difference values; acquiring the absolute value of the maximum feature difference value from the absolute values of the k-1 feature difference values, and recording the absolute value as the maximum feature difference value;

judging whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent or not according to whether the maximum characteristic difference is not larger than a difference threshold or not;

wherein k is a natural number, and i belongs to [0, k ].

2. The method for checking the steady-state and dynamic electrical quantity data of the regional power grid according to claim 1, wherein the step of performing feature extraction processing on the steady-state sequence, the dynamic sequence or the difference sequence to obtain a corresponding steady-state feature matrix, a corresponding dynamic feature matrix or a corresponding difference feature matrix comprises:

performing inverse cosine processing on each normalized data in the steady-state sequence, the dynamic sequence or the difference sequence to obtain k angle data;

performing inner product processing on any two angle data in the steady-state sequence, the dynamic sequence or the difference sequence to obtain k x k characteristic data;

and forming a steady-state feature matrix, a dynamic feature matrix or a difference feature matrix of k rows and k columns by using k x k feature data corresponding to the steady-state sequence, the dynamic sequence or the difference sequence.

3. The method for checking the steady-state and dynamic electrical quantity data of the regional power grid according to claim 1, wherein determining whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent according to whether the maximum characteristic difference is not greater than a difference threshold comprises:

if the maximum characteristic difference value is not larger than the difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent, and the steady-state and dynamic electrical quantity data of the regional power grid are checked;

if the maximum characteristic difference value is larger than the difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are inconsistent, and difference processing is carried out on all the characteristic values of any two adjacent steady-state characteristic sequences and any two adjacent dynamic characteristic sequences to obtain the absolute values of k-1 steady-state characteristic difference values and the absolute values of k-1 dynamic characteristic difference values; acquiring a corresponding maximum steady-state feature difference value and a maximum dynamic feature difference value from the absolute values of the k-1 steady-state feature difference values and the absolute values of the k-1 dynamic feature difference values, and recording the maximum steady-state feature difference value and the maximum dynamic feature difference value as the maximum steady-state feature difference value and the maximum dynamic feature difference value;

and judging whether the checking of the steady state and dynamic electrical quantity data of the regional power grid is finished or not according to whether the maximum steady state characteristic difference value is not smaller than a difference threshold or not and whether the maximum dynamic characteristic difference value is not larger than the difference threshold or not.

4. The method for checking steady-state and dynamic electrical quantity data of the regional power grid according to claim 3, comprising:

if the maximum steady-state characteristic difference value is not smaller than a difference threshold value and the maximum dynamic characteristic difference value is not larger than the difference threshold value, the steady-state electrical quantity data has bad data, and the checking of the steady-state and dynamic electrical quantity data of the regional power grid is completed;

if the maximum steady-state feature difference value is smaller than a difference threshold value and the maximum dynamic feature difference value is larger than a difference threshold value, whether the checking of the steady-state and dynamic electrical quantity data of the regional power grid is finished or not is judged again according to whether the maximum steady-state feature difference value is not larger than the difference threshold value and whether the maximum dynamic feature difference value is not smaller than the difference threshold value.

5. The method for checking steady-state and dynamic electrical quantity data of the regional power grid according to claim 4, comprising:

if the maximum steady-state characteristic difference value is not larger than a difference threshold value and the maximum dynamic characteristic difference value is not smaller than the difference threshold value, the dynamic electrical quantity data has bad data, and the steady-state and dynamic electrical quantity data check of the regional power grid is completed;

if the maximum steady-state feature difference value is larger than the difference threshold value and the maximum dynamic feature difference value is smaller than the difference threshold value, whether the checking of the steady-state and dynamic electrical quantity data of the regional power grid is finished or not is judged again according to whether the maximum steady-state feature difference value is not smaller than the difference threshold value and whether the maximum dynamic feature difference value is not smaller than the difference threshold value.

6. The method for checking steady-state and dynamic electrical quantity data of the regional power grid according to claim 5, comprising:

and if the maximum steady-state characteristic difference value is not smaller than a difference threshold value and the maximum dynamic characteristic difference value is not smaller than a difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data both have bad data, and the steady-state and dynamic electrical quantity data check of the regional power grid is completed.

7. The method for checking the steady-state and dynamic electrical quantity data of the regional power grid according to claim 1, wherein the steady-state data sequence or the dynamic data sequence is a data sequence arranged from a time corresponding to sampling of the 1 st electrical quantity data to a time corresponding to sampling of the kth electrical quantity data.

8. The method according to claim 1, wherein the difference threshold is 0.01.

9. A device for checking steady-state and dynamic electrical quantity data of a regional power grid is characterized by comprising a data acquisition module, a data sequence module, a characteristic sequence module, a difference processing module and a judgment module;

the data acquisition module is used for performing discrete sampling on a steady-state signal of the regional power grid at a first sampling frequency to obtain a steady-state data sequence consisting of k pieces of steady-state electrical quantity data; discrete sampling is carried out on the dynamic signal of the regional power grid at a second sampling frequency, and a dynamic data sequence consisting of k dynamic electrical quantity data is obtained;

the data sequence module is configured to perform difference processing on the ith steady-state electrical quantity data in the steady-state data sequence and the ith dynamic electrical quantity data in the dynamic data sequence to obtain a difference data sequence composed of k difference data;

the sequence module is used for carrying out normalization processing on the steady-state data sequence, the dynamic data sequence and the difference data sequence to obtain a corresponding steady-state sequence, a corresponding dynamic sequence and a corresponding difference sequence;

the characteristic sequence module is used for extracting characteristics of the steady-state sequence, the dynamic sequence and the difference sequence to obtain a corresponding steady-state characteristic matrix, a corresponding dynamic characteristic matrix and a corresponding difference characteristic matrix; calculating the characteristic values of the steady-state characteristic matrix, the dynamic characteristic matrix and the difference characteristic matrix to obtain a corresponding steady-state characteristic sequence, a corresponding dynamic characteristic sequence and a corresponding difference characteristic sequence which are formed by k characteristic values;

the difference processing module is used for performing difference processing on all the feature values of any two adjacent difference values in the difference feature sequence to obtain the absolute values of k-1 feature difference values; acquiring the absolute value of the maximum feature difference value from the absolute values of the k-1 feature difference values, and recording the absolute value as the maximum feature difference value;

the judging module is used for judging whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent or not according to whether the maximum characteristic difference is not larger than a difference threshold or not;

wherein k is a natural number, and i belongs to [0, k ].

10. The equipment for checking the steady-state and dynamic electrical quantity data of the regional power grid is characterized by comprising a processor and a memory;

the memory is used for storing program codes and transmitting the program codes to the processor;

the processor is configured to execute the method for checking the steady-state and dynamic electrical quantity data of the regional power grid according to any one of claims 1 to 8 according to instructions in the program code.

Background

With the development of the power grid automation technology, the number of PMU power management units at the substation end and RTU devices at the remote terminal unit gradually increases, and the quality requirement thereof also becomes higher and higher. The RTU device can only provide steady-state, low-sampling-density and asynchronous power grid time section information; the PMU power management unit, although capable of performing synchronous measurements on the electrical system on a time scale of the order of milliseconds, is not yet able to completely replace the SCADA system of the grid under the conditions of the prior art.

In a quite long time, the situation that the SCADA system and the PMU power management unit coexist and supplement each other appears in the power grid system. However, whether the steady-state data and the dynamic data are on the side of a power grid system or the side of a transformer substation, the steady-state data and the dynamic data are possibly interfered by various uncertain factors, so that errors occur in the acquired data, and the method has great significance in checking, checking and identifying the wrong data.

In the current steady-state and dynamic data checking scheme for the power grid, the difference of dynamic-steady-state data is calculated respectively, and whether error data exists is determined by judging the difference between the difference and a manually set threshold. However, the dynamic-steady data are not aligned in time format at first, in addition, the extracted difference value is a linear characteristic, the checking and identifying capability for error data is limited, the method is highly dependent on the size of a threshold value, and the manual setting difficulty is high. Moreover, the checking mode is a checking method based on state estimation of a power grid and a power transformation stage, but the state estimation method is complex in modeling and high in implementation difficulty, dynamic-steady state time sections are different, and the dynamic-steady state time sections cannot be fully fused in state estimation, so that the checking method is poor in practicability.

Disclosure of Invention

The embodiment of the invention provides a method, a device and equipment for checking steady-state and dynamic electrical quantity data of a regional power grid, which are used for solving the technical problems of low checking accuracy and large workload in the conventional method for checking the steady-state and dynamic electrical quantity data of the power grid.

In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:

a method for checking steady-state and dynamic electrical quantity data of a regional power grid comprises the following steps:

carrying out discrete sampling on a steady-state signal of the regional power grid at a first sampling frequency to obtain a steady-state data sequence consisting of k steady-state electrical quantity data; discrete sampling is carried out on the dynamic signal of the regional power grid at a second sampling frequency, and a dynamic data sequence consisting of k dynamic electrical quantity data is obtained;

performing difference processing on the ith steady-state electrical quantity data in the steady-state data sequence and the ith dynamic electrical quantity data in the dynamic data sequence to obtain a difference value data sequence consisting of k difference value data;

normalizing the steady-state data sequence, the dynamic data sequence and the difference data sequence to obtain a corresponding steady-state sequence, a corresponding dynamic sequence and a corresponding difference sequence;

performing feature extraction processing on the steady-state sequence, the dynamic sequence and the difference sequence to obtain a corresponding steady-state feature matrix, a corresponding dynamic feature matrix and a corresponding difference feature matrix; calculating the characteristic values of the steady-state characteristic matrix, the dynamic characteristic matrix and the difference characteristic matrix to obtain a corresponding steady-state characteristic sequence, a corresponding dynamic characteristic sequence and a corresponding difference characteristic sequence which are formed by k characteristic values;

performing difference processing on all any two adjacent characteristic values in the difference characteristic sequence to obtain absolute values of k-1 characteristic difference values; acquiring the absolute value of the maximum feature difference value from the absolute values of the k-1 feature difference values, and recording the absolute value as the maximum feature difference value;

judging whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent or not according to whether the maximum characteristic difference is not larger than a difference threshold or not;

wherein k is a natural number, and i belongs to [0, k ].

Preferably, the step of performing feature extraction processing on the steady-state sequence, the dynamic sequence, or the difference sequence to obtain a corresponding steady-state feature matrix, a corresponding dynamic feature matrix, or a corresponding difference feature matrix includes:

performing inverse cosine processing on each normalized data in the steady-state sequence, the dynamic sequence or the difference sequence to obtain k angle data;

performing inner product processing on any two angle data in the steady-state sequence, the dynamic sequence or the difference sequence to obtain k x k characteristic data;

and forming a steady-state feature matrix, a dynamic feature matrix or a difference feature matrix of k rows and k columns by using k x k feature data corresponding to the steady-state sequence, the dynamic sequence or the difference sequence.

Preferably, the determining whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent according to whether the maximum characteristic difference is not greater than a difference threshold includes:

if the maximum characteristic difference value is not larger than the difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent, and the steady-state and dynamic electrical quantity data of the regional power grid are checked;

if the maximum characteristic difference value is larger than the difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are inconsistent, and difference processing is carried out on all the characteristic values of any two adjacent steady-state characteristic sequences and any two adjacent dynamic characteristic sequences to obtain the absolute values of k-1 steady-state characteristic difference values and the absolute values of k-1 dynamic characteristic difference values; acquiring a corresponding maximum steady-state feature difference value and a maximum dynamic feature difference value from the absolute values of the k-1 steady-state feature difference values and the absolute values of the k-1 dynamic feature difference values, and recording the maximum steady-state feature difference value and the maximum dynamic feature difference value as the maximum steady-state feature difference value and the maximum dynamic feature difference value;

and judging whether the checking of the steady state and dynamic electrical quantity data of the regional power grid is finished or not according to whether the maximum steady state characteristic difference value is not smaller than a difference threshold or not and whether the maximum dynamic characteristic difference value is not larger than the difference threshold or not.

Preferably, the method for checking the steady-state and dynamic electrical quantity data of the regional power grid comprises the following steps:

if the maximum steady-state characteristic difference value is not smaller than a difference threshold value and the maximum dynamic characteristic difference value is not larger than the difference threshold value, the steady-state electrical quantity data has bad data, and the checking of the steady-state and dynamic electrical quantity data of the regional power grid is completed;

if the maximum steady-state feature difference value is smaller than a difference threshold value and the maximum dynamic feature difference value is larger than a difference threshold value, whether the checking of the steady-state and dynamic electrical quantity data of the regional power grid is finished or not is judged again according to whether the maximum steady-state feature difference value is not larger than the difference threshold value and whether the maximum dynamic feature difference value is not smaller than the difference threshold value.

Preferably, the method for checking the steady-state and dynamic electrical quantity data of the regional power grid comprises the following steps:

if the maximum steady-state characteristic difference value is not larger than a difference threshold value and the maximum dynamic characteristic difference value is not smaller than the difference threshold value, the dynamic electrical quantity data has bad data, and the steady-state and dynamic electrical quantity data check of the regional power grid is completed;

if the maximum steady-state feature difference value is larger than the difference threshold value and the maximum dynamic feature difference value is smaller than the difference threshold value, whether the checking of the steady-state and dynamic electrical quantity data of the regional power grid is finished or not is judged again according to whether the maximum steady-state feature difference value is not smaller than the difference threshold value and whether the maximum dynamic feature difference value is not smaller than the difference threshold value.

Preferably, the method for checking the steady-state and dynamic electrical quantity data of the regional power grid comprises the following steps: and if the maximum steady-state characteristic difference value is not smaller than a difference threshold value and the maximum dynamic characteristic difference value is not smaller than a difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data both have bad data, and the steady-state and dynamic electrical quantity data check of the regional power grid is completed.

Preferably, the steady-state data sequence or the dynamic data sequence is a data sequence arranged from a time corresponding to sampling of the 1 st electrical quantity data to a time corresponding to sampling of the kth electrical quantity data.

Preferably, the difference threshold is 0.01.

The invention also provides a device for checking the steady-state and dynamic electrical quantity data of the regional power grid, which comprises a data acquisition module, a data sequence module, a characteristic sequence module, a difference processing module and a judgment module;

the data acquisition module is used for performing discrete sampling on a steady-state signal of the regional power grid at a first sampling frequency to obtain a steady-state data sequence consisting of k pieces of steady-state electrical quantity data; discrete sampling is carried out on the dynamic signal of the regional power grid at a second sampling frequency, and a dynamic data sequence consisting of k dynamic electrical quantity data is obtained;

the data sequence module is configured to perform difference processing on the ith steady-state electrical quantity data in the steady-state data sequence and the ith dynamic electrical quantity data in the dynamic data sequence to obtain a difference data sequence composed of k difference data;

the sequence module is used for carrying out normalization processing on the steady-state data sequence, the dynamic data sequence and the difference data sequence to obtain a corresponding steady-state sequence, a corresponding dynamic sequence and a corresponding difference sequence;

the characteristic sequence module is used for extracting characteristics of the steady-state sequence, the dynamic sequence and the difference sequence to obtain a corresponding steady-state characteristic matrix, a corresponding dynamic characteristic matrix and a corresponding difference characteristic matrix; calculating the characteristic values of the steady-state characteristic matrix, the dynamic characteristic matrix and the difference characteristic matrix to obtain a corresponding steady-state characteristic sequence, a corresponding dynamic characteristic sequence and a corresponding difference characteristic sequence which are formed by k characteristic values;

the difference processing module is used for performing difference processing on all the feature values of any two adjacent difference values in the difference feature sequence to obtain the absolute values of k-1 feature difference values; acquiring the absolute value of the maximum feature difference value from the absolute values of the k-1 feature difference values, and recording the absolute value as the maximum feature difference value;

the judging module is used for judging whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent or not according to whether the maximum characteristic difference is not larger than a difference threshold or not;

wherein k is a natural number, and i belongs to [0, k ].

The invention also provides a device for checking the steady-state and dynamic electrical quantity data of the regional power grid, which comprises a processor and a memory;

the memory is used for storing program codes and transmitting the program codes to the processor;

the processor is used for executing the steady-state and dynamic electrical quantity data checking method of the regional power grid according to the instructions in the program codes.

According to the technical scheme, the embodiment of the invention has the following advantages: the method comprises the steps of obtaining the same amount of steady-state electrical quantity data and dynamic electrical quantity data of the regional power grid to form a corresponding steady-state data sequence and a dynamic data sequence, subtracting the steady-state data sequence and the dynamic data sequence to obtain a difference data sequence, sequentially normalizing the steady-state data sequence, the dynamic data sequence and the difference data sequence, extracting features, calculating the feature values to obtain a corresponding steady-state feature sequence, a dynamic feature sequence and a difference feature sequence, subtracting the feature values of any two adjacent feature values in the difference feature sequence to obtain the absolute value of the value, selecting the absolute value of the maximum feature difference value as the maximum feature difference value, comparing the maximum feature difference value with a difference threshold value to identify whether the steady-state electrical quantity data is consistent with the dynamic electrical quantity data or not, and checking and identifying the data. The method for checking the steady-state and dynamic electrical quantity data of the regional power grid can extract the steady-state and dynamic time correlation characteristics by acquiring the data at different moments according to the sampling frequency, can reduce the redundancy of the data, can effectively identify the bad data of the steady-state electrical quantity data and the dynamic electrical quantity data, has small calculated amount and short consumed time, is more reliable than the result of checking by only using single-source data, and solves the technical problems of low checking accuracy and large workload of the existing method for checking the steady-state and dynamic electrical quantity data of the power grid.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.

Fig. 1 is a flowchart illustrating steps of a method for checking steady-state and dynamic electrical quantity data of a regional power grid according to an embodiment of the present invention.

Fig. 2 is a flowchart of the step of feature extraction of the steady-state and dynamic electrical quantity data checking method for the regional power grid according to the embodiment of the present invention.

Fig. 3 is a flowchart illustrating another step of a method for checking steady-state and dynamic electrical quantity data of a local power grid according to an embodiment of the present invention.

Fig. 4 is a block diagram of a device for checking steady-state and dynamic electrical quantity data of a regional power grid according to an embodiment of the present invention.

Detailed Description

In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The embodiment of the application provides a method, a device and equipment for checking steady-state and dynamic electrical quantity data of a regional power grid, and is used for solving the technical problems of low checking accuracy and large workload in the existing checking mode of the steady-state and dynamic electrical quantity data of the power grid.

The first embodiment is as follows:

fig. 1 is a flowchart illustrating steps of a method for checking steady-state and dynamic electrical quantity data of a regional power grid according to an embodiment of the present invention.

As shown in fig. 1, an embodiment of the present invention provides a method for checking steady-state and dynamic electrical quantity data of a local power grid, including the following steps:

s10, performing discrete sampling on a steady-state signal of the regional power grid at a first sampling frequency to obtain a steady-state data sequence consisting of k steady-state electrical quantity data; and carrying out discrete sampling on the dynamic signal of the regional power grid at a second sampling frequency to obtain a dynamic data sequence consisting of k dynamic electrical quantity data.

It should be noted that the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are mainly acquired, and a steady-state data sequence and a dynamic data sequence are established. In the embodiment, the electric quantities such as voltage, current, active power, reactive power and the like in the steady-state signal of the regional power grid are sampled at the first sampling frequency Δ T_sCarrying out discrete sampling to obtain steady-state electrical quantity data, and recording the steady-state electrical quantity data of the 1 st sampling as x_s(0ΔT_s) And the k-th sampled steady-state electrical quantity data is recorded as x_s(kΔT_s) Then the steady state data sequence X_s(k) Is a data sequence arranged from the time corresponding to the sampling of the 1 st steady-state electrical quantity data to the time corresponding to the sampling of the kth steady-state electrical quantity data, namely X_s(k)＝[x_s(0),x_s(ΔT_s),x_s(2ΔT_s),…,x_s(kΔT_s)]. The electric quantities of voltage, current, active power, reactive power and the like in the dynamic signals of the regional power grid are sampled at a second sampling frequency delta T_pDiscrete sampling is carried out to obtain dynamic electrical quantity data, and the 1 st sampled dynamic electrical quantity data is recorded as x_p(0ΔT_p) And the k-th sampled dynamic electrical quantity data is recorded as x_p(kΔT_p) Then dynamic data sequence X_p(k) Is a data sequence arranged from the time corresponding to the sampling of the 1 st dynamic electrical quantity data to the time corresponding to the sampling of the kth dynamic electrical quantity data, namely x_p(k)＝[x_p(0)，x_p(ΔT_p)，x_p(2ΔT_p)，…，x_p(kΔT_p)]. Wherein k is a natural number.

In the embodiment of the present invention, the steady-state electrical quantity data is electrical quantity data collected by the RTU, and the dynamic data refers to electrical quantity data collected by the PMU.

And S20, carrying out difference processing on the ith steady-state electrical quantity data in the steady-state data sequence and the ith dynamic electrical quantity data in the dynamic data sequence to obtain a difference value data sequence consisting of k difference value data.

The step S20 is mainly to perform difference processing on the data obtained in the step S10. In the present embodiment, the difference data sequence composed of k difference data is X_d(k) That is toAnd S30, normalizing the steady-state data sequence, the dynamic data sequence and the difference data sequence to obtain the corresponding steady-state sequence, dynamic sequence and difference sequence.

It should be noted that, in step S30, the normalization process is mainly performed on the values in the three sequences of the steady-state data sequence, the dynamic data sequence, and the difference data sequence to obtain the steady-state sequenceDynamic sequenceSum and difference sequenceScaling the value of (1) to [ -1, 1 [ ]]The above. In the embodiment of the present invention, the formula of the normalization process is:

in the formula (I), the compound is shown in the specification,for a steady-state data sequence X_s(k) The largest element in (1);for dynamic data sequence X_p(k) The largest element in (1);for a difference data sequence X_d(k) The largest element in (1);for a steady-state data sequence X_s(k) The smallest element in the list;for dynamic data sequence X_p(k) The smallest element in the list;for a difference data sequence X_d(k) The smallest element in the list.

S40, performing feature extraction processing on the steady-state sequence, the dynamic sequence and the difference sequence to obtain a corresponding steady-state feature matrix, a corresponding dynamic feature matrix and a corresponding difference feature matrix; and calculating the characteristic values of the steady-state characteristic matrix, the dynamic characteristic matrix and the difference characteristic matrix to obtain a corresponding steady-state characteristic sequence, a dynamic characteristic sequence and a difference characteristic sequence which are formed by k characteristic values.

In step S40, a feature matrix is mainly created from the normalized data, feature values composed of the ith feature matrix are calculated, and a feature sequence is composed of the k feature values obtained by calculation. In this example, the steady state signature sequence is recordedDynamic signature sequenceThe characteristic sequence of the difference is recorded as

S50, performing difference processing on all any two adjacent characteristic values in the difference characteristic sequence to obtain absolute values of k-1 characteristic difference values; and acquiring the absolute value of the maximum feature difference value from the absolute values of the k-1 feature difference values, and recording the absolute value as the maximum feature difference value.

And S60, judging whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent or not according to whether the maximum characteristic difference is not larger than the difference threshold or not.

In step S50 and step S60, the difference between any two adjacent feature values in the difference feature sequence obtained in step S40 is mainly performed to obtain a feature difference value, that is, the feature difference value is obtainedThen, the absolute value of the feature difference is taken, and the largest numerical value is selected from the absolute values of the k-1 feature differences to be used as the maximum feature differenceFinally, according to the maximum characteristic difference valueWhether the difference value is not more than the threshold value is judged to judge the steady-state electricity of the regional power gridAnd whether the quantity data is consistent with the dynamic electrical quantity data or not is judged, and the checking of the stable state and the dynamic electrical quantity data of the regional power grid is realized. In this embodiment, the difference threshold is preferably 0.01.

The invention provides a method for checking steady-state and dynamic electric quantity data of a regional power grid, which comprises the steps of obtaining the same amount of steady-state electric quantity data and dynamic electric quantity data of the regional power grid to form a corresponding steady-state data sequence and a dynamic data sequence, subtracting the steady-state data sequence and the dynamic data sequence to obtain a difference data sequence, sequentially normalizing the steady-state data sequence, the dynamic data sequence and the difference data sequence, extracting features, calculating feature values to obtain a corresponding steady-state feature sequence, a dynamic feature sequence and a difference feature sequence, subtracting the feature values of any two adjacent feature values in the difference feature sequence to obtain the absolute value of the value, selecting the absolute value of the maximum feature difference value as the maximum feature difference value, comparing the maximum feature difference value with a difference threshold value to identify whether the steady-state electric quantity data is consistent with the dynamic electric quantity data or not, and checking and identifying the data. The method for checking the steady-state and dynamic electrical quantity data of the regional power grid can extract the steady-state and dynamic time correlation characteristics by acquiring the data at different moments according to the sampling frequency, can reduce the redundancy of the data, can effectively identify the bad data of the steady-state electrical quantity data and the dynamic electrical quantity data, has small calculated amount and short consumed time, is more reliable than the result of checking by only using single-source data, and solves the technical problems of low checking accuracy and large workload of the existing method for checking the steady-state and dynamic electrical quantity data of the power grid.

It should be noted that the steady-state and dynamic electrical quantity data checking method for the regional power grid is applied to a power grid dispatching side or inside a transformer substation to realize the checking of steady-state and dynamic data, and the steady-state and dynamic electrical quantity data checking method for the regional power grid has the advantages of self-adaptive data checking, reduction of manual workload, higher reliability and universality. The method for checking the steady-state and dynamic electrical quantity data of the regional power grid greatly improves the capability of feature extraction by carrying out nonlinear transformation on the dynamic electrical quantity data and the steady-state electrical quantity data.

Fig. 2 is a flowchart of the step of feature extraction of the steady-state and dynamic electrical quantity data checking method for the regional power grid according to the embodiment of the present invention.

As shown in fig. 2, in an embodiment of the present invention, in step S40, the step of performing feature extraction processing on the steady-state sequence, the dynamic sequence, or the difference sequence to obtain a corresponding steady-state feature matrix, dynamic feature matrix, or difference feature matrix includes:

s41, performing inverse cosine processing on each normalized data in the steady-state sequence, the dynamic sequence or the difference sequence to obtain k angle data;

s42, performing inner product processing on any two angle data in the steady-state sequence, the dynamic sequence or the difference sequence to obtain k x k characteristic data;

and S43, forming a steady-state feature matrix, a dynamic feature matrix or a difference feature matrix of k rows and k columns by using k × k feature data corresponding to the steady-state sequence, the dynamic sequence or the difference sequence.

In the embodiment of the present invention, the feature extraction processing on the steady-state sequence, the dynamic sequence, or the difference sequence is mainly performed according to that data in the steady-state sequence, the dynamic sequence, or the difference sequence is obtained at different times through the same sampling frequency, and therefore, the data in the steady-state sequence, the dynamic sequence, or the difference sequence has a sequence value and a timestamp (i Δ T) corresponding to the value. In the present embodiment, values representing time stamps and sequences are expressed in terms of angles and radii toFor example, the content of feature extraction is:

and (3) calculating the radius, wherein the calculation formula is as follows:

calculating the angle, and dividing the interval [0, 1 ]]Dividing into N equal parts to obtain N +1 separation points. Then discard 0 and continuously associate these points with a time series, the ith steady stateAngle data phi of the sequence_s(i) Is defined as:to better mine the relationship between sequences from angles, any two angle data are inner product processed, i.e. areφ_s(j) For the angle data of the jth steady-state sequence, i and j both belong to k. On this basis, one can obtain: steady-state feature matrix G corresponding to steady-state sequence_sNamely:

the same can also be applied to dynamic sequencesSum and difference sequencePerforming the above transformation to obtain phi_p(i)、φ_d(i) And G_p、G_d。

Fig. 3 is a flowchart illustrating another step of a method for checking steady-state and dynamic electrical quantity data of a local power grid according to an embodiment of the present invention.

As shown in fig. 3, in one embodiment of the present invention, in step S60, determining whether the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent according to whether the maximum characteristic difference is not greater than the difference threshold includes:

if the maximum characteristic difference value is not larger than the difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are consistent, and the steady-state and dynamic electrical quantity data of the regional power grid are checked;

if the maximum characteristic difference value is larger than the difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data of the regional power grid are inconsistent, and difference processing is carried out on all the characteristic values of any two adjacent steady-state characteristic sequences and dynamic characteristic sequences to obtain the absolute values of k-1 steady-state characteristic difference values and the absolute values of k-1 dynamic characteristic difference values; acquiring a corresponding maximum steady-state feature difference value and a maximum dynamic feature difference value from the absolute values of the k-1 steady-state feature difference values and the absolute values of the k-1 dynamic feature difference values, and recording the maximum steady-state feature difference value and the maximum dynamic feature difference value as the maximum steady-state feature difference value and the maximum dynamic feature difference value;

judging whether the checking of the steady state and dynamic electrical quantity data of the regional power grid is finished or not according to whether the maximum steady state feature difference value is not smaller than the difference threshold value or not and whether the maximum dynamic feature difference value is not larger than the difference threshold value or not;

if the maximum steady-state characteristic difference value is not smaller than the difference threshold value and the maximum dynamic characteristic difference value is not larger than the difference threshold value, the steady-state electrical quantity data has bad data, and the checking of the steady-state and dynamic electrical quantity data of the regional power grid is completed;

if the maximum steady-state feature difference value is smaller than the difference threshold value and the maximum dynamic feature difference value is larger than the difference threshold value, judging whether the checking of the steady-state and dynamic electrical quantity data of the regional power grid is finished or not according to whether the maximum steady-state feature difference value is not larger than the difference threshold value and whether the maximum dynamic feature difference value is not smaller than the difference threshold value;

if the maximum steady-state characteristic difference value is not greater than the difference threshold value and the maximum dynamic characteristic difference value is not less than the difference threshold value, the dynamic electrical quantity data has bad data, and the steady-state and dynamic electrical quantity data check of the regional power grid is completed;

if the maximum steady-state feature difference value is larger than the difference threshold value and the maximum dynamic feature difference value is smaller than the difference threshold value, judging whether the checking of the steady-state and dynamic electrical quantity data of the regional power grid is finished or not according to whether the maximum steady-state feature difference value is not smaller than the difference threshold value and whether the maximum dynamic feature difference value is not smaller than the difference threshold value;

and if the maximum steady-state characteristic difference value is not less than the difference threshold value and the maximum dynamic characteristic difference value is not less than the difference threshold value, the steady-state electrical quantity data and the dynamic electrical quantity data both have bad data, and the steady-state and dynamic electrical quantity data check of the regional power grid is completed.

In an embodiment of the present invention, the maximum steady state characteristic difference isMaximum dynamic characteristic difference of

Example two:

fig. 4 is a block diagram of a device for checking steady-state and dynamic electrical quantity data of a regional power grid according to an embodiment of the present invention.

As shown in fig. 4, an embodiment of the present invention further provides a device for checking steady-state and dynamic electrical quantity data of a regional power grid, including a data acquisition module 10, a data sequence module 20, a sequence module 30, a feature sequence module 40, a difference processing module 50, and a determination module 60;

the data acquisition module 10 is configured to perform discrete sampling on a steady-state signal of the regional power grid at a first sampling frequency to obtain a steady-state data sequence composed of k pieces of steady-state electrical quantity data; discrete sampling is carried out on the dynamic signal of the regional power grid at a second sampling frequency, and a dynamic data sequence consisting of k dynamic electrical quantity data is obtained;

a data sequence module 20, configured to perform difference processing on the ith steady-state electrical quantity data in the steady-state data sequence and the ith dynamic electrical quantity data in the dynamic data sequence to obtain a difference data sequence composed of k difference data;

the sequence module 30 is configured to perform normalization processing on the steady-state data sequence, the dynamic data sequence, and the difference data sequence to obtain a corresponding steady-state sequence, a corresponding dynamic sequence, and a corresponding difference sequence;

the characteristic sequence module 40 is configured to perform characteristic extraction processing on the steady-state sequence, the dynamic sequence, and the difference sequence to obtain a corresponding steady-state characteristic matrix, a corresponding dynamic characteristic matrix, and a corresponding difference characteristic matrix; calculating the characteristic values of the steady-state characteristic matrix, the dynamic characteristic matrix and the difference characteristic matrix to obtain a corresponding steady-state characteristic sequence, a corresponding dynamic characteristic sequence and a corresponding difference characteristic sequence which are formed by k characteristic values;

a difference processing module 50, configured to perform difference processing on all arbitrary two adjacent feature values in the difference feature sequence to obtain absolute values of k-1 feature difference values; acquiring the absolute value of the maximum feature difference value from the absolute values of the k-1 feature difference values, and recording the absolute value as the maximum feature difference value;

the judging module 60 is configured to judge whether the steady-state electrical quantity data of the regional power grid is consistent with the dynamic electrical quantity data according to whether the maximum characteristic difference is not greater than the difference threshold;

wherein k is a natural number, and i belongs to [0, k ].

It should be noted that the modules in the second embodiment correspond to the steps in the first embodiment, and the steps in the first embodiment have been described in detail in the first embodiment, and the contents of the modules in the second embodiment are not described in detail in this second embodiment.

Example three:

the embodiment of the invention provides a device for checking steady-state and dynamic electrical quantity data of a regional power grid, which comprises a processor and a memory;

a memory for storing the program code and transmitting the program code to the processor;

and the processor is used for executing the steady-state and dynamic electrical quantity data checking method of the regional power grid according to the instructions in the program codes.

It should be noted that the processor is configured to execute the steps in the above-mentioned one embodiment of the method for checking the steady-state and dynamic electrical quantity data of the regional power grid according to the instructions in the program code. Alternatively, the processor, when executing the computer program, implements the functions of each module/unit in each system/apparatus embodiment described above.

Illustratively, a computer program may be partitioned into one or more modules/units, which are stored in a memory and executed by a processor to accomplish the present application. One or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of a computer program in a terminal device.

The terminal device may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that the terminal device is not limited and may include more or fewer components than those shown, or some components may be combined, or different components, e.g., the terminal device may also include input output devices, network access devices, buses, etc.

The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The storage may be an internal storage unit of the terminal device, such as a hard disk or a memory of the terminal device. The memory may also be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the terminal device. Further, the memory may also include both an internal storage unit of the terminal device and an external storage device. The memory is used for storing computer programs and other programs and data required by the terminal device. The memory may also be used to temporarily store data that has been output or is to be output.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.