CN109284936B - Power quality evaluation method based on cloud image visual output - Google Patents

Power quality evaluation method based on cloud image visual output Download PDF

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CN109284936B
CN109284936B CN201811181786.6A CN201811181786A CN109284936B CN 109284936 B CN109284936 B CN 109284936B CN 201811181786 A CN201811181786 A CN 201811181786A CN 109284936 B CN109284936 B CN 109284936B
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丁凯
李伟
胡羽川
钱一民
王易
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Electric Power Research Institute of State Grid Hubei Electric Power Co Ltd
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Abstract

The invention provides a cloud graphic visual output-based power quality evaluation method, which comprises the following steps: determining power quality evaluation indexes needing to be subjected to graphic visualization to form a power quality comprehensive evaluation index system; calculating and determining the influence of each index in an index system on a final evaluation result by utilizing an analytic hierarchy process, namely the weight of the index; calculating the normalized value of the original data of each evaluation index; calculating visual output parameters of the electric energy quality evaluation result; substituting the parameters into the Gaussian function, and drawing a function image of the Gaussian function with the parameters by using common mathematical software in a computer, wherein the drawn image is a visual cloud graph of the final evaluation result. The method establishes an electric energy quality evaluation model based on cloud graphic visual output, overcomes the problems of non-uniform measurement standard and obscure data of the traditional electric power data, and can help electric power users to intuitively and specifically grasp the electric energy quality condition of self power consumption.

Description

Power quality evaluation method based on cloud image visual output
Technical Field
The invention relates to the technical field of power quality evaluation and decision assistance at a user side, in particular to a power quality evaluation method based on cloud graphic visual output.
Background
With the development of the distributed power supply technology, more and more power electronic devices are applied to a power grid, the nonlinear factors in the power grid are increased, and the electric energy distortion is more and more; meanwhile, along with the application of the frequency conversion energy-saving technology in air conditioners, refrigerators, air purifiers, dish washing machines, kitchen pulverizers and other appliances, more and more electric energy quality pollution sources are available on the user side; the quality of electric energy in the power grid is increasingly threatened due to the simultaneous action of various factors. If the power quality is in a problem, the electric appliance of a user is damaged if the power quality is small, the energy consumption is increased, some precise instruments cannot work if the power quality is large, normal production and technical development of the society are hindered, and the power quality has attracted great attention of power departments and users.
With the progress of power grid technology, smart meters and precise sensing devices are installed more and more in the power grid, and a large amount of power data are accumulated. However, it is very difficult to define the quality of the current power in a digital form through massive data. The existing power quality determination rule cannot completely cover multi-aspect data, the data presentation mode is obscure, non-professionals cannot understand the data, and users are very concerned about the power quality of the users, which is always a problem barrier between power departments and the users.
Disclosure of Invention
The invention provides a cloud graphic visualization-based electric energy quality evaluation method, which aims to solve the problems that the current electric energy quality evaluation lacks a uniform standard, an evaluation result cannot be visually displayed, and a power consumer cannot visually grasp the self-power consumption electric energy quality condition.
The invention is realized by adopting the following technical scheme:
a graphical visualization power quality assessment method comprises the following steps:
step 1, determining power quality evaluation indexes needing graphic visualization to form a power quality comprehensive evaluation index system;
step 2, calculating and determining the influence of each index in an index system on a final evaluation result by using an analytic hierarchy process, namely the weight of the index;
step 3, calculating the normalization value of the original data of each evaluation index;
step 4, calculating the visual output parameters of the power quality evaluation result: a height parameter, a weighted deviation parameter, a concentration parameter;
and 5, substituting the parameters into the Gaussian function, drawing a function image by using common mathematical software in a computer, wherein the drawn image is the visual cloud graph of the final evaluation result.
Further, the index system in step 1 covers: (1) voltage quality index: voltage deviation, voltage fluctuation, voltage flicker, voltage waveform distortion rate and three-phase voltage unbalance rate; (2) frequency quality index: frequency deviation; (3) the reliability index is as follows: and power supply reliability.
Further, the method for determining the weight of the index in step 2 includes:
(1) and constructing a judgment matrix. The n indexes contained in the system are compared pairwise to obtain an n-order judgment matrix formed by the comparison results of the two indexes:
Figure BDA0001825175290000021
in the formula, aijRepresenting the relative importance of the ith and jth objects, aij1 means that index i is equally important with respect to index j; a isij3 indicates that index i is slightly important relative to index j; a isij5 means that index i is significantly important relative to index j; a isij7 indicates that index i is strongly important relative to index j; a isij9 indicates that index i is extremely important relative to index j;
(2) checking the consistency of the judgment matrix: calculated using the following formula:
Figure BDA0001825175290000022
Figure BDA0001825175290000031
in the formula, λmaxIs the maximum characteristic root of the matrix A, and n is the order number of the matrix; CI is the intermediate process quantity, RI is the allowable range of consistency deviation, and the larger the numerical value is, the larger the inconsistency deviation of the allowable judgment matrix is; CR<0.1, the consistency check is passed, otherwise, the importance of the indexes needs to be compared again to form a new judgment matrix;
(3) and (3) calculating index weight: firstly, calculating the product M of each row element of the judgment matrix Ai：
Figure BDA0001825175290000032
Calculating MiRoot of square ni*：
Figure BDA0001825175290000033
And finally, normalization treatment:
Figure BDA0001825175290000034
then calculated WiWhich is the weight of the ith index of the n indices.
Further, RI can take any value between 0.58 and 1.45.
Further, the step 3 specifically includes:
the indexes of the quality of each electric energy are normalized according to the following calculation formula:
Figure BDA0001825175290000035
in the formula, ESiThe magnitude of the normalized index for the ith index, EiFor the ith index in the data acquisition and collection systemOriginal value, EIiThe standard value of the national or enterprise power quality standard of the ith index.
Further, the step 4 of calculating the height parameter, the weighted deviation parameter and the concentration parameter includes the following specific steps:
the height parameter represents the historical best value in the index, and the height parameter H is calculated by the formula:
H＝max{Ei}(19)
the weighted deviation degree represents the deviation position of the current comprehensive evaluation result and a standard value, and the calculation formula is as follows:
Figure BDA0001825175290000041
the concentration ratio represents the original data quantity provided by the current data acquisition system for the comprehensive evaluation index system, and the calculation formula is as follows:
Figure BDA0001825175290000042
in the formula, Num represents the amount of data which needs to be graphically and visually output and is sent by the electric energy data acquisition system.
Further, the step 5 specifically includes the following steps:
the height parameter H, the weighted deviation parameter θ, the concentration parameter S are substituted into the amplitude a, the expectation b and the variance c in the gaussian function to form a cloud function, where a is H, b is 1- θ, and c is S, a function image of x with respect to f (x) is drawn, the function image is a cloud graph, which is a visual output of the power quality evaluation result, and the gaussian function is expressed as follows:
Figure BDA0001825175290000043
the invention has the beneficial effects that: the method has the advantages of clear data requirement, simple calculation, easy operation and guiding effect on the auxiliary decision of the power quality evaluation. Meanwhile, the final result visual output graph comprises three information, namely a numerical value of a best historical index, the deviation of the current evaluation result and a standard result and the utilization amount of original data in the evaluation process, so that a user can read the data more intuitively, and the user can conveniently master the quality level of the current used electric energy.
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FIG. 1 is a schematic flow chart diagram illustrating a graphical visualization power quality assessment method according to an embodiment of the present invention;
FIG. 2 is a power quality assessment index system employed in an embodiment of the present invention;
fig. 3 is a cloud graph and a standard cloud graph of the final output evaluation result in the embodiment of the present invention.
Detailed Description
The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings.
The embodiment provides an electric energy quality evaluation method for cloud graphic visual output, which helps a power user to intuitively and simply master the quality condition of own electric energy. Firstly, establishing an electric energy quality evaluation index system, wherein indexes covered by the system can be selected from voltage deviation, voltage fluctuation, voltage flicker, voltage waveform distortion rate, three-phase voltage unbalance rate, frequency deviation and power supply reliability; determining the weight of each index in result evaluation by using an analytic hierarchy process; normalizing the value of each index by utilizing normalization calculation; calculating height, weighted cheapness and concentration parameters of the output graph by using a cloud graph parameter calculation formula; and substituting the parameters by using a Gaussian function, and drawing an image based on the Gaussian function, wherein the image is the visualized output result of the power quality evaluation content. The method can simply and directly help the user to master the quality condition of the electric energy, and timely reflect and adjust the quality condition to a power supply enterprise under the condition of unsatisfactory quality.
One embodiment of the power quality evaluation method based on cloud graphic visual output comprises the following steps:
step 1, determining power quality evaluation indexes needing graphic visualization to form a power quality comprehensive evaluation index system. The index system may encompass: (1) voltage quality index: voltage deviation, voltage fluctuation, voltage flicker, voltage waveform distortion rate and three-phase voltage unbalance rate; (2) frequency quality index: frequency deviation; (3) the reliability index is as follows: and power supply reliability. The indexes are all commonly used assessment indexes of the current power supply department.
And 2, determining the influence of each index in the index system on the final evaluation result, namely the weight of the index. The weight determination process can adopt an analytic hierarchy process, and the calculation process of the method comprises the following steps:
(1) and constructing a judgment matrix. The n indexes contained in the system are compared pairwise to obtain an n-order judgment matrix formed by the comparison results of the two indexes:
Figure BDA0001825175290000061
in the formula, aijIndicating the relative importance of the ith target to the jth target. a isij1 means that index i is equally important with respect to index j; a isij3 indicates that index i is slightly important relative to index j; a isij5 means that index i is significantly important relative to index j; a isij7 indicates that index i is strongly important relative to index j; a isijThe index i is extremely important relative to the index j as indicated by 9.
(2) And checking the consistency of the judgment matrix. Calculated using the following formula:
Figure BDA0001825175290000062
Figure BDA0001825175290000063
in the formula, λmaxIs the maximum characteristic root of the matrix A, and n is the order number of the matrix; CI is intermediate process quantity, RI is consistency deviation allowable range, and can take any value between 0.58-1.45, and the larger the numerical value is, the non-judgment of the matrix is allowedThe greater the variance in consistency. CR<And 0.1, passing the consistency check, otherwise, comparing the importance of the indexes again and forming a new judgment matrix.
(3) And calculating index weight. Firstly, calculating the product M of each row element of the judgment matrix Ai：
Figure BDA0001825175290000064
Calculating MiRoot of square ni*：
Figure BDA0001825175290000065
And finally, normalization treatment:
Figure BDA0001825175290000071
then calculated WiWhich is the weight of the ith index of the n indices.
And 3, determining the normalized value of each evaluation index. In a data acquisition system, the indexes of the quality of each electric energy have different values and different qualified standards, and need to be normalized according to the following calculation formula:
Figure BDA0001825175290000072
in the formula, ESiThe magnitude of the normalized index for the ith index, EiIs the original value, EI, of the ith index in the data acquisition systemiThe standard value of the national or enterprise power quality standard of the ith index.
And 4, calculating the visual output parameters of the final power quality evaluation result. The cloud graphic parameters of the visual output comprise: height, weighted deviation and concentration.
The height parameter represents the historical best value in the index. The height parameter H is calculated by the formula:
H＝max{Ei} (8’)
the weighted deviation degree represents the deviation position of the current comprehensive evaluation result and the standard value. The calculation formula is as follows:
Figure BDA0001825175290000073
the concentration ratio represents the original data volume provided by the current data acquisition system for the comprehensive evaluation index system. The calculation formula is as follows:
Figure BDA0001825175290000074
in the formula, Num represents the amount of data which needs to be graphically and visually output and is sent by the electric energy data acquisition system.
The visualized output parameters of the comprehensive evaluation result of the power quality can be calculated by utilizing the three formulas. Meanwhile, in order to highlight the comparison effect, a power grid enterprise can calculate and provide a set of standard visual output parameters for a user according to the ideal power quality, and can be used for providing comparison for the calculation result of the user side.
And 5, visually outputting the result. And substituting the height parameter H, the weighted deviation parameter theta and the concentration parameter S into the amplitude a in the Gaussian function, expecting b and the variance c to form a cloud function, and enabling a to be H, b to be 1-theta and c to be S. And drawing a function image of x relative to f (x), wherein the function image is a cloud graph, and is the visual output of the power quality evaluation result. Therefore, the user can visually see the level of the electric energy used by the user. The gaussian function is expressed as follows:
Figure BDA0001825175290000081
example 1
A power quality assessment method based on cloud graphic visualization output is disclosed, as shown in FIG. 1, and comprises the following steps:
A. and determining the power quality evaluation index needing to be subjected to graphic visualization to form a power quality comprehensive evaluation index system. The index system covers: (1) voltage quality index: voltage deviation, voltage fluctuation, voltage flicker, voltage waveform distortion rate and three-phase voltage unbalance rate; (2) frequency quality index: frequency deviation; (3) the reliability index is as follows: and power supply reliability. The total number of the indexes is 3 types and 7 indexes.
B. And (4) calculating and determining the influence of each index in the index system on the final evaluation result, namely the weight of the index by using the formula (1 '-6').
C. The normalized value of each evaluation index is calculated and determined using equation (7').
D. And calculating the visual output parameters of the electric energy quality evaluation result. The height parameter is calculated by equation (8 '), the weighted deviation parameter is calculated by equation (9 '), and the concentration parameter is calculated by equation (10 ').
E. The parameters are taken to be gaussian in formula (11'), where a is H, b is 1- θ, and c is S. And drawing the Gaussian function with the parameters by using common mathematical software in a computer, such as MATLAB, and finishing the visual graphical output of the evaluation result. The graphics are sent to the user side screen device so that the user can visually see at what level the quality of the power he or she is using is approximately.
Example 2
I. Determining the power quality evaluation index needing to be subjected to graphic visualization to form a power quality comprehensive evaluation index system, wherein the power quality comprehensive evaluation index system comprises the following steps: (1) voltage quality index: voltage deviation, voltage fluctuation, voltage flicker, voltage waveform distortion rate and three-phase voltage unbalance rate; (2) frequency quality index: frequency deviation; (3) the reliability index is as follows: and power supply reliability. The index system is shown in figure 2.
And II, calculating and determining the influence of each index in the index system on the final evaluation result, namely the weight of the index by using the formula (1 '-6'). The weights are shown in table 1.
Table 1 index weight of electric energy quality evaluation index system
Figure BDA0001825175290000091
Figure BDA0001825175290000101
The normalized values of the respective evaluation indexes were calculated and determined using formula (7'), and the calculation results are shown in table 2.
Table 2 index normalization value of power quality evaluation index system
Index name Normalized value
Deviation of voltage 0.0890
Voltage fluctuation 0.0029
Voltage flicker 0.0032
Rate of distortion of voltage waveform 0.0033
Unbalance rate of three-phase voltage 0.0921
Frequency deviation 0.0014
Reliability of power supply 0.0052
And IV, calculating the visual output parameters of the electric energy quality evaluation result. The height parameter is calculated by equation (8 '), the weighted deviation parameter is calculated by equation (9 '), and the concentration parameter is calculated by equation (10 '). And (3) calculating the result: the height parameter is 1.0, the weighted deviation parameter is 0.2730, and the concentration parameter is 0.0486.
V. the gaussian function with the parameter in equation (11'), where a is 1.0, b is 0.2730, and c is 0.0486. And (4) finishing the visual graphic output of the evaluation result by using the Gaussian function with the parameters by using common mathematical software MATLAB in a computer. The output cloud pattern and the standard evaluation cloud pattern are shown in fig. 3. The graphics are sent to the user side screen device so that the user can visually see at what level the quality of the power he or she is using is approximately.
It should be understood that parts of the specification not set forth in detail are well within the prior art.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (5)

1. A power quality assessment method based on cloud image visual output is characterized by comprising the following steps:
step 1, determining power quality evaluation indexes needing graphic visualization to form a power quality comprehensive evaluation index system;
step 2, calculating and determining the influence of each index in an index system on a final evaluation result by using an analytic hierarchy process, namely the weight of the index;
step 3, calculating the normalization value of the original data of each evaluation index;
step 4, calculating the visual output parameters of the power quality evaluation result: a height parameter, a weighted deviation parameter, a concentration parameter;
step 5, substituting the parameters into a Gaussian function, drawing a function image by using common mathematical software in a computer, wherein the drawn image is a visual cloud graph of a final evaluation result;
the step 4 of calculating the height parameter, the weighted deviation parameter and the concentration parameter comprises the following specific steps:
the height parameter represents the historical best value in the index, and the height parameter H is calculated by the formula:
H＝max{Ei} (1)
in the formula, EiThe original value of the ith index in the data acquisition system;
the weighted deviation degree represents the deviation position of the current comprehensive evaluation result and a standard value, and the calculation formula is as follows:
Figure FDA0003376942410000011
in the formula, ESiValue of the index normalized for the ith index, wiIs the weight of the ith index;
the concentration ratio represents the original data quantity provided by the current data acquisition system for the comprehensive evaluation index system, and the calculation formula is as follows:
Figure FDA0003376942410000021
in the formula, Num represents the quantity of data which is sent by the electric energy data acquisition system and needs to be subjected to graphic visual output;
the step 5 specifically comprises the following steps:
the height parameter H, the weighted deviation parameter θ, the concentration parameter S are substituted into the amplitude a, the expectation b and the variance c in the gaussian function to form a cloud function, where a is H, b is 1- θ, and c is S, a function image of x with respect to f (x) is drawn, the function image is a cloud graph, which is a visual output of the power quality evaluation result, and the gaussian function is expressed as follows:
Figure FDA0003376942410000022
2. the power quality assessment method based on cloud graphic visualization output according to claim 1, wherein: the index system in the step 1 covers: (1) voltage quality index: voltage deviation, voltage fluctuation, voltage flicker, voltage waveform distortion rate and three-phase voltage unbalance rate; (2) frequency quality index: frequency deviation; (3) the reliability index is as follows: and power supply reliability.
3. The power quality assessment method based on cloud graphic visualization output according to claim 1, wherein: the method for determining the weight of the index in the step 2 comprises the following steps:
(1) constructing a judgment matrix: the n indexes contained in the system are compared pairwise to obtain an n-order judgment matrix formed by the comparison results of the two indexes:
Figure FDA0003376942410000023
in the formula, aijRepresenting the relative importance of the ith and jth objects, aij1 means that index i is equally important with respect to index j; a isij3 indicates that index i is slightly important relative to index j; a isij5 means that index i is significantly important relative to index j; a isij7 indicates that index i is strongly important relative to index j; a isij9 indicates that index i is extremely important relative to index j;
(2) checking the consistency of the judgment matrix: calculated using the following formula:
Figure FDA0003376942410000031
Figure FDA0003376942410000032
in the formula, λmaxIs the maximum characteristic root of the matrix A, and n is the order number of the matrix; CI is the intermediate process quantity, RI is the allowable range of consistency deviation, and the larger the numerical value is, the larger the inconsistency deviation of the allowable judgment matrix is; CR<0.1, the consistency check is passed, otherwise, the importance of the indexes needs to be compared again to form a new judgment matrix;
(3) and (3) calculating index weight: firstly, calculating the product M of each row element of the judgment matrix Ai：
Figure FDA0003376942410000033
Calculating MiRoot of square ni*：
Figure FDA0003376942410000034
And finally, normalization treatment:
Figure FDA0003376942410000035
then calculated wiWhich is the weight of the ith index of the n indices.
4. The cloud graphics visualization output-based power quality assessment method according to claim 3, wherein: RI takes any value between 0.58 and 1.45.
5. The power quality assessment method based on cloud graphic visualization output according to claim 1, wherein: the step 3 specifically comprises the following steps:
the indexes of the quality of each electric energy are normalized according to the following calculation formula:
Figure FDA0003376942410000041
in the formula, ESiThe magnitude of the normalized index for the ith index, EiIs the original value, EI, of the ith index in the data acquisition systemiThe standard value of the national or enterprise power quality standard of the ith index.
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