CN114862229A - Power quality evaluation method and device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to a power quality evaluation method, a power quality evaluation device, computer equipment and a storage medium. The method comprises the following steps: acquiring a pre-constructed power quality evaluation system corresponding to a region to be evaluated; obtaining evaluation index data of a plurality of monitoring points in the area to be evaluated according to the power quality evaluation system; normalizing the evaluation index data to obtain standardized index data; performing combined weighting calculation on the standardized index data to obtain a combined index weight corresponding to the standardized index data; and comprehensively evaluating the combined index weight and the standardized index data to obtain an electric energy quality evaluation result of the area to be evaluated. By adopting the method, the time complexity of power quality evaluation can be reduced, and the power quality evaluation efficiency is improved.
Description
Technical Field
The present application relates to the field of power technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for evaluating power quality.
Background
With the rapid development of modern power systems, in order to stably use a green and environment-friendly renewable energy power generation technology, a power distribution network is connected to a large-scale distributed power supply, the number of nonlinear loads is increasing day by day, and solving the problem of power quality of the power grid becomes a primary task of improving the power utilization condition of users on the power grid side. In addition, the large-scale grid connection of modern power electronic equipment and high-precision instruments further deteriorates the power quality problem of a power grid, aggravates the contradiction between the supply and demand of the power grid, and further causes additional economic loss and loss of high-precision equipment. Therefore, the method has scientific and rigorous comprehensive evaluation on the power quality, reflects the overall condition of the power quality of the power grid, and has great significance for comprehensively evaluating the power quality of the power grid under the power market environment, formulating high-quality power price and researching a power quality control model.
In the traditional mode, comprehensive evaluation of the power quality is carried out on the basis of a probabilistic neural network. However, the training process of the probabilistic neural network is complex, and takes a lot of time, resulting in low efficiency of power quality assessment.
Disclosure of Invention
In view of the above, it is necessary to provide a power quality assessment method, a device, a computer apparatus, a computer readable storage medium, and a computer program product, which can improve the efficiency of power quality assessment, in view of the above technical problems.
In a first aspect, the present application provides a power quality assessment method. The method comprises the following steps:
acquiring a pre-constructed power quality evaluation system corresponding to a region to be evaluated;
acquiring evaluation index data of a plurality of monitoring points in an area to be evaluated according to an electric energy quality evaluation system;
normalizing the evaluation index data to obtain standardized index data;
performing combined weighting calculation on the standardized index data to obtain a combined index weight corresponding to the standardized index data;
and comprehensively evaluating the combined index weight and the standardized index data to obtain the electric energy quality evaluation result of the area to be evaluated.
In one embodiment, the comprehensive evaluation of the combined index weight and the standardized index data to obtain the power quality evaluation result of the area to be evaluated comprises:
calculating distance weighting sum data corresponding to each monitoring point according to the combined index weight, the standardized index data and a preset calculation relation;
carrying out standardization processing on the distance weighted sum data to obtain distance weighted sum standard data;
and carrying out mean value calculation on the distance weighting and the standard data to obtain the electric energy quality evaluation result of the area to be evaluated.
In one embodiment, calculating distance weighted sum data corresponding to each monitoring point according to the combined index weight, the normalized index data and a preset calculation relationship includes:
calculating an average solution reference value of each power quality evaluation index corresponding to the standardized index data according to a preset calculation relation;
calculating an ideal solution distance of the standardized index data according to a preset calculation relation and the average solution reference value;
and weighting and calculating the ideal solution distance of the standardized index data corresponding to each monitoring point according to the preset calculation relationship and the combined index weight to obtain distance weighted sum data corresponding to each monitoring point.
In one embodiment, the performing combined weighting calculation on the normalized index data to obtain a combined index weight corresponding to the normalized index data includes:
performing hierarchical analysis processing on the power quality assessment indexes corresponding to the standardized index data to obtain subjective weights corresponding to the standardized index data;
performing entropy weight calculation on the standardized index data to obtain objective weight corresponding to the standardized index data;
and calculating the combined index weight corresponding to the standardized index data according to the subjective weight, the objective weight and the preset weight relation.
In one embodiment, normalizing the evaluation index data to obtain normalized index data includes:
calculating the ratio of the evaluation index data to the corresponding preset index threshold;
and determining the calculated ratio as the standard index data.
In one embodiment, the obtaining of the pre-constructed power quality assessment system corresponding to the region to be assessed includes:
acquiring monitoring data of a plurality of monitoring points in an area to be evaluated;
determining power quality evaluation indexes according to the monitoring data of the monitoring points and the key load types corresponding to the monitoring points;
and constructing a power quality evaluation system corresponding to the area to be evaluated according to the power quality evaluation index.
In a second aspect, the application further provides an electric energy quality assessment device. The device includes:
the evaluation system acquisition module is used for acquiring a pre-constructed electric energy quality evaluation system corresponding to the area to be evaluated;
the index data acquisition module is used for acquiring evaluation index data of a plurality of monitoring points in the area to be evaluated according to the power quality evaluation system;
the normalization processing module is used for performing normalization processing on the evaluation index data to obtain standardized index data;
the combined weighting calculation module is used for performing combined weighting calculation on the standardized index data to obtain a combined index weight corresponding to the standardized index data;
and the electric energy quality evaluation module is used for comprehensively evaluating the combined index weight and the standardized index data to obtain an electric energy quality evaluation result of the area to be evaluated.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the steps of the above-described method embodiments when executing the computer program.
In a fourth aspect, the present application further provides a computer-readable storage medium. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned embodiments of the method.
In a fifth aspect, the present application further provides a computer program product. Computer program product comprising a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
According to the power quality assessment method, the power quality assessment device, the computer equipment, the storage medium and the computer program product, the pre-constructed power quality assessment system corresponding to the region to be assessed is obtained, and the assessment index data of the multiple monitoring points in the region to be assessed are obtained according to the power quality assessment system. The evaluation index data is normalized to obtain standardized index data, and dimensions among different indexes can be eliminated. The standardized index data is subjected to combined weighted calculation to obtain combined index weights corresponding to the standardized index data, objective and reasonable evaluation can be performed on the standardized index data, time complexity in the power quality evaluation process is reduced, power quality evaluation efficiency is improved, and influences of artificial subjective factors are reduced as far as possible. Meanwhile, the combined index weight and the standardized index data are comprehensively evaluated to obtain the electric energy quality evaluation result of the area to be evaluated, the electric energy quality grade of each monitoring point in the area to be evaluated can be obtained, and the power price making requirement and the high requirement on electric energy quality evaluation of the power distribution network with continuously increased scale are met.
Drawings
FIG. 1 is a diagram illustrating an exemplary embodiment of a power quality assessment method;
FIG. 2 is a schematic flow chart of a power quality assessment method according to an embodiment;
FIG. 3 is a schematic diagram of an electrical energy quality assessment system in one embodiment;
FIG. 4 is a flowchart illustrating the step of comprehensively evaluating the combined metric weight and the normalized metric data according to one embodiment;
FIG. 5 is a schematic flow chart of a power quality assessment method according to another embodiment;
FIG. 6 is a block diagram showing the construction of a power quality evaluating apparatus according to an embodiment;
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The traditional method is to carry out comprehensive evaluation on the power quality based on a probabilistic neural network. However, the training process of the probabilistic neural network is complex, needs to be relearned for different topologies, and needs very detailed historical data, which takes a lot of time, resulting in low efficiency of power quality assessment.
In order to solve the technical problem, a power quality evaluation method is provided.
The power quality evaluation method provided by the embodiment of the application can be applied to the application environment shown in fig. 1. Wherein the server 102 is in communication with a plurality of monitoring devices 104. The monitoring device 104 is used for collecting data of the corresponding monitoring point. The monitoring points refer to nodes in the power grid. One monitoring point may correspond to at least one monitoring device. The server 102 obtains a pre-constructed power quality evaluation system corresponding to the area to be evaluated, determines evaluation index data of a plurality of monitoring points in the area to be evaluated in data collected by the monitoring device 104 according to the power quality evaluation system, so as to normalize the evaluation index data and obtain standardized index data, performs combined weighting calculation on the standardized index data to obtain combined index weights corresponding to the standardized index data, and further performs comprehensive evaluation on the combined index weights and the standardized index data to obtain a power quality evaluation result of the area to be evaluated. The server 102 may be implemented as a stand-alone server or a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, a power quality assessment method is provided, which is described by taking the method as an example applied to the server in fig. 1, and includes the following steps:
The power quality evaluation system is composed of a plurality of indexes capable of reflecting the power quality characteristics of monitoring points. The construction of a power quality evaluation system is the basis of power quality evaluation. The power quality evaluation system may be hereinafter simply referred to as an evaluation system.
The evaluation system can be constructed by the server in advance aiming at the area to be evaluated. Specifically, a plurality of monitoring points are arranged in the area to be evaluated, the monitoring points refer to nodes in the power grid, and each monitoring point can correspond to at least one monitoring device. The monitoring equipment is used for acquiring monitoring data of the corresponding monitoring points. The monitoring data refers to all relevant data of the monitoring points, such as voltage deviation, subharmonics and the like. The server acquires monitoring data of a plurality of monitoring points acquired by monitoring equipment in the area to be evaluated, so that indexes which can comprehensively and accurately reflect the power quality condition of the area to be evaluated and cover various power quality problems possibly occurring in the area to be evaluated are selected as power quality evaluation indexes according to the acquired monitoring data, and an evaluation system shown in fig. 3 is further constructed. Wherein, THD U Representing the total harmonic distortion rate, I 2-7 Denotes the 2 nd to 7 th harmonic, I 11 Denotes the 11 th harmonic, I 13 Representing the 13 th harmonic. The evaluation system thus obtained may comprise the voltage deviation Δ U, the voltage flicker P It Unbalanced three phases xi U Total harmonic distortion rate THD U 2 nd-7 th harmonic I 2-7 11 th harmonic I 11 13 th harmonic I 13 And waiting for a plurality of electric energy quality evaluation indexes.
When the server performs power quality evaluation, a pre-constructed evaluation system corresponding to the area to be evaluated can be directly obtained, so that the power quality evaluation can be performed on the area to be evaluated according to the evaluation system.
And 204, acquiring evaluation index data of a plurality of monitoring points in the area to be evaluated according to the power quality evaluation system.
The evaluation system comprises a plurality of power quality evaluation indexes, so that the server can select corresponding evaluation index data from the monitoring data acquired by each monitoring device according to the power quality evaluation indexes to obtain the evaluation index data of a plurality of monitoring points in the area to be evaluated.
And step 206, normalizing the evaluation index data to obtain standardized index data.
The electric energy quality evaluation index has incoordinability due to different dimensions, so that the evaluation index data needs to be normalized to eliminate the dimensions. In assessment studies, indices are generally divided into cost-type indices and benefit-type indices. The cost index reflects the correlation between the index and the required cost, so the smaller the cost index, the better. The benefit index reflects the relevance between the index and the created benefit, so the greater the benefit index is, the better the benefit index is. The power quality evaluation index is one of cost indexes, and normalization processing can be performed according to a normalization calculation formula of the cost indexes. The advantage of this normalization is that all normalization results are in the range of [0,1], and the calculation formula is as follows:
wherein the content of the first and second substances,
denotes x i Normalized value of (A), X i For the ith power quality assessment index, x i For the electric energy quality evaluation index X i Evaluation index data of (1), x i,max Is x i Maximum value of (a), x i,min Is x i Is measured.
Further, the normalization processing mode can also be that the ratio calculation is directly carried out on the evaluation index data and the corresponding preset index threshold value; and determining the calculated ratio as the standard index data. The preset index threshold may be a limit value specified in a relevant standard of the power quality assessment index, or may be a value specified by combining an actual condition of the area to be assessed and the relevant standard of the power quality assessment index. The calculation formula of the normalization method can be as follows:
wherein the content of the first and second substances,
denotes x i Normalized value of (a), x i For the electric energy quality evaluation index X i Evaluation index data of (1), x i,lim For the electric energy quality evaluation index X i The preset index threshold value. x is the number of i For the electric energy quality evaluation index X i The evaluation index data of (1).
The normalization processing mode has the advantage that whether the single power quality evaluation index exceeds the standard can be directly judged. When the normalization result is more than 1, the power quality evaluation index exceeds the standard, and the unqualified power quality of the area to be evaluated can be directly judged. If the normalization result is less than or equal to 1, it indicates that the power quality evaluation index does not exceed the standard, and the power quality evaluation is performed according to the power quality evaluation method in the embodiment.
And step 208, performing combined weighting calculation on the standardized index data to obtain a combined index weight corresponding to the standardized index data.
The combined weighting calculation is to calculate a combined index weight corresponding to the standardized index data by combining the subjective weight and the objective weight corresponding to the standardized index data.
The server can perform hierarchical analysis processing on the power quality assessment indexes corresponding to the standardized index data, so that subjective weights corresponding to the standardized index data are obtained. And the subjective weight corresponding to the standardized index data is the subjective weight of the power quality assessment index corresponding to the standardized index data. For example, the subjective weight corresponding to the normalized index data may be calculated by AHP (analytical Hierarchy Process). And the server performs entropy weight calculation on the standardized index data to obtain the objective weight corresponding to the standardized index data. The objective weight corresponding to the standardized index data is the objective weight of the power quality assessment index corresponding to the standardized index data. For example, an entropy weight method may be used to calculate an objective weight corresponding to the normalized index data. And the server further calculates the combined index weight corresponding to the standardized index data according to the subjective weight, the objective weight and the preset weight relation. The preset weight relationship refers to a calculation formula of the combined index weight.
And step 210, comprehensively evaluating the combined index weight and the standardized index data to obtain an electric energy quality evaluation result of the area to be evaluated.
The server can calculate distance weighted sum data corresponding to the standardized index data according to the combined index weight and the standardized index data, so that the distance weighted sum data is subjected to mean value calculation, and an electric energy quality evaluation result of the area to be evaluated is obtained. For example, the evaluation based on distance from average solution (EDAS) method may be used to comprehensively evaluate the combined index weight and the normalized index data. After the power quality assessment result of the area to be assessed is obtained, relevant personnel can check the power quality assessment result and give a targeted treatment suggestion or an improvement suggestion.
In the power quality assessment method, the pre-constructed assessment system corresponding to the area to be assessed is obtained, and the assessment index data of the monitoring points in the area to be assessed is obtained according to the assessment system. The evaluation index data is normalized to obtain standardized index data, and dimensions among different indexes can be eliminated. The standardized index data is subjected to combined weighted calculation to obtain combined index weights corresponding to the standardized index data, objective and reasonable evaluation can be performed on the standardized index data, time complexity in the power quality evaluation process is reduced, power quality evaluation efficiency is improved, and influences of artificial subjective factors are reduced as far as possible. Meanwhile, the combined index weight and the standardized index data are comprehensively evaluated to obtain the electric energy quality evaluation result of the area to be evaluated, the electric energy quality grade of each monitoring point in the area to be evaluated can be obtained, and the power price making requirement and the high requirement on electric energy quality evaluation of the power distribution network with continuously increased scale are met.
In an embodiment, as shown in fig. 4, the comprehensively evaluating the combined index weight and the normalized index data to obtain the power quality evaluation result of the area to be evaluated includes:
and 402, calculating distance weighting sum data corresponding to each monitoring point according to the combined index weight, the standardized index data and a preset calculation relation.
And 406, performing mean value calculation on the distance weighting and the standard data to obtain an electric energy quality evaluation result of the area to be evaluated.
The preset calculation relationship refers to a calculation formula of distance weighting sum data.
The server may calculate an ideal solution distance of the normalized index data according to a preset calculation relationship. Wherein the ideal solution distance may include a positive ideal solution distance PDA and a negative ideal solution distance NDA. And weighting and calculating the ideal solution distance of the standardized index data corresponding to each monitoring point according to the preset calculation relationship and the combined index weight to obtain distance weighted sum data corresponding to each monitoring point. Wherein the distance weighted sum data may comprise a positive distance weighted sum SP i Sum negative distance weighted sum SN i . Positive distance weighted sum SP i Is obtained by weighting and calculating the positive ideal solution distance PDA, the weighted sum SN of the negative distances i Is calculated by weighting and calculating the negative ideal solution distance NDA. The server weights and calculates the ideal solution distance according to the preset calculation relationship and the combined index weight, and the consideration of the weight characteristic enables the subsequent electric energy quality evaluation result to be more reasonable.
Further, calculating distance weighting and data corresponding to each monitoring point according to the combined index weight, the standardized index data and a preset calculation relationship comprises: calculating an average solution reference value of each monitoring point corresponding to the standardized index data according to a preset calculation relation; calculating an ideal solution distance of the standardized index data according to a preset calculation relation and the average solution reference value; and weighting and calculating the ideal solution distance of the standardized index data corresponding to each monitoring point according to the preset calculation relationship and the combined index weight to obtain distance weighted sum data corresponding to each monitoring point.
The preset calculation relationship may include an average solution reference value calculation formula, an ideal solution distance calculation formula, and a distance weighting and data calculation formula.
And the server calculates an average solution reference value corresponding to the standardized index data according to an average solution reference value calculation formula. The average solution reference value may be an average value of the normalized index data corresponding to each power quality assessment index. The average value is used as a reference value, the optimal solution can be close to be evaluated, and the electric energy quality evaluation result is more accurate. The average solution reference value calculation formula may be as follows:
AV＝[AV j ] 1×n (3)
where AV represents the average solution reference value, AV j And the average solution reference value of the jth power quality evaluation index is represented, and n represents the number of the power quality evaluation indexes.
And the server calculates the ideal solution distance of the standardized index data according to the ideal solution distance calculation formula and the average solution reference value. The ideal solution distance calculation formula can be as follows:
PDA represents positive ideal solution distance of standardized index data, NDA represents negative ideal solution distance of standardized index data, PDA ij Represents the positive ideal solution distance, NDA, of the jth power quality assessment index in the ith monitoring point ij The negative ideal solution distance of the jth power quality evaluation index in the ith monitoring point is represented, m represents the number of the monitoring points, n represents the number of the power quality evaluation indexes, and W represents the number of the power quality evaluation indexes ij Normalized index data, AV, representing the jth power quality assessment index at the ith monitoring point j And the average solution reference value of the jth power quality evaluation index is represented.
It should be noted that the power quality assessment indexes corresponding to the standardized index data of each monitoring point are the same, and the arrangement modes of the standardized index data in each monitoring point are the same and are all arranged in a one-to-one correspondence manner according to the power quality indexes. For example, the first power quality assessment indicators corresponding to the standardized indicator data of the plurality of monitoring points are the same, and the corresponding second power quality assessment indicators are also the same.
Further, the server may arrange the standardized index data of the plurality of monitoring points correspondingly according to the power quality evaluation index to form an evaluation matrix, which may be as follows:
the number of rows in the evaluation matrix W represents the number of monitoring points, and the number of columns represents the number of power quality evaluation indexes in each monitoring point. It is understood that the server may calculate the ideal solution distance of the normalized index data in the evaluation index according to the ideal solution distance calculation formula and the average solution reference value. M in the above ideal solution distance formula (4) may represent the number of rows of the evaluation matrix, and n may represent the number of columns of the evaluation matrix.
The server can also carry out weighting and calculation on the ideal solution distance of the standardized index data corresponding to each monitoring point according to a distance weighting and data calculation formula and the combined index weight to obtain distance weighting and data corresponding to each monitoring point. The distance weighting and data calculation formula may be as follows:
wherein, SP i Representing a weighted sum of positive distances, SN, corresponding to each monitored point i Representing a weighted sum of negative distances, ω, corresponding to each monitored point j Combined index weight representing jth power quality assessment index, PDA ij Represents the positive ideal solution distance, NDA, of the jth power quality assessment index in the ith monitoring point ij And the negative ideal solution distance of the jth power quality evaluation index in the ith monitoring point is represented.
The server can perform standardized processing on the distance weighting and data, and subsequent sequencing calculation is facilitated. The calculation formula of the normalization process can be as follows:
wherein NSP i Representing positive distance weighted criterion data, NSN i Representing negative distance weighted sum standard data.
And the server calculates the distance weighting and the average value of the standard data to obtain the power quality evaluation value of each monitoring point. The calculation formula of the power quality assessment value is as follows:
wherein E is i Representing the power quality assessment value of each monitoring point，NSP i Positive distance weighted sum standard data, NSN, representing each monitoring point i Negative distance weighted and normalized data for each monitoring point is shown.
Then, the server sorts the calculated power quality assessment values of the multiple monitoring points to obtain a power quality assessment result of the area to be assessed, for example, ranking can be performed according to the power quality assessment values to obtain power quality assessment ranks corresponding to the monitoring points. The server can also determine the power quality grade of each monitoring point according to the calculated power quality assessment value. Specifically, the server may compare the power quality assessment value with a preset power quality level range, so as to determine the power quality level of each monitoring point. Therefore, the embodiment can calculate the power quality grade of each monitoring point and can obtain the power quality sequence of each monitoring point.
In this embodiment, distance weighting and data corresponding to each monitoring point are calculated according to the combined index weight, the normalized index data, and a preset calculation relationship. And then, carrying out standardization processing on the distance weighted sum data to obtain distance weighted sum standard data, and further carrying out mean value calculation on the distance weighted sum standard data to obtain the electric energy quality evaluation result of the area to be evaluated. The weight characteristic is fully considered, so that the power quality evaluation result is more reasonable and accurate. According to the embodiment, the power quality grades of all the monitoring points can be calculated, the power quality ranking of all the monitoring points can be obtained, and the continuously-increased power price making requirement of the power distribution network and the high requirement for power quality evaluation are met.
In one embodiment, performing combined weighting calculation on the normalized index data to obtain a combined index weight corresponding to the normalized index data includes: performing hierarchical analysis processing on the power quality assessment indexes corresponding to the standardized index data to obtain subjective weights corresponding to the standardized index data; performing entropy weight calculation on the standardized index data to obtain objective weight corresponding to the standardized index data; and calculating the combined index weight corresponding to the standardized index data according to the subjective weight, the objective weight and the preset weight relation.
In the process of power quality evaluation, if only an entropy weight method is adopted to calculate the index weight, the importance degree of the index itself can be ignored to a certain extent, and sometimes the determined index weight is far from the expected result. Meanwhile, the dimension of the index cannot be reduced by the entropy weight method, and even if the entropy weight method conforms to the mathematical rule and has strict mathematical significance, the subjective intention of a decision maker is often ignored. Therefore, the embodiment adopts a combination weighting method considering expert opinions to calculate the combination index weight corresponding to the standardized index data. The combined weighting method considering the expert opinions may include a subjective weighting method and an objective weighting method. The subjective weighting method may adopt AHP (Analytic Hierarchy Process), and the objective weighting method may adopt an entropy weighting method.
Specifically, the server may obtain a scoring table of the importance of a plurality of experts on the power quality assessment index. The scoring table can be obtained by scoring the importance of the power quality assessment index by a plurality of experts according to the actual situation and the scoring scale of the area to be assessed. For example, the scoring scale may be as shown in the following table:
TABLE 1 Scale of points
| Scale | Degree of importance |
| 1 | Of equal importance |
| 3、1/3 | More important/less important |
| 5、1/5 | Very important/very unimportant |
| 7、1/7 | Of particular importance/of particular unimportance |
| 9、1/9 | Extremely important/extremely unimportant |
And the server forms a judgment matrix A according to the grading meter and the power quality evaluation indexes in the evaluation system. And calculating the maximum eigenvalue and the maximum eigenvector of the judgment matrix. For example, the maximum eigenvalue and the maximum eigenvector of the determination matrix may be calculated according to the existing calculation method of the maximum eigenvalue and the maximum eigenvector. And carrying out consistency check on the judgment matrix, and if the check is passed, carrying out normalization processing on the maximum eigenvector to obtain the subjective weight corresponding to the standardized index data. And if the verification fails, multiple experts are required to mark again to obtain a new marking table, and consistency verification is performed again until the consistency verification passes. Further, in the consistency check process, the server calculates a consistency index value of the judgment matrix, and the calculation formula may be as follows: then, the calculation formula for judging the consistency index value CI of the matrix a is as follows:
wherein CI represents the consistency index value of the judgment matrix, lambda max Represents the maximum eigenvalue of the decision matrix and n represents the order of the decision matrix a.
And the server identifies and judges whether the consistency index value of the matrix meets a preset constraint condition. Wherein the preset constraint condition may be
RI represents average random consistency index corresponding to each power quality evaluation indexThe recommended values, RI values, can be shown in the following table:
TABLE 2 RI values
And if the preset constraint condition is met, the verification is passed. If the preset constraint condition is not met, the verification is not passed.
Since the normalization index data is obtained by normalizing the evaluation index data according to the above formula (1) or (2), the entropy weight calculation can be directly performed on the normalization index data in the process of calculating the objective weight. In the process of performing entropy weight calculation on the standardized index data by the server, the entropy value of each power quality evaluation index corresponding to the standardized index data can be calculated first. The formula for calculating the entropy value can be as follows:
wherein D is ij And the index value proportion of the standardized index data corresponding to the jth power quality evaluation index in the ith monitoring point is represented. X' ij Expressing the standardized index data corresponding to the jth power quality evaluation index in the ith monitoring point, wherein m represents the number of the monitoring points, and e j And expressing the entropy value of the jth power quality evaluation index.
And the server calculates the entropy weight corresponding to the standardized index data according to the entropy value of each power quality evaluation index, so as to obtain the objective weight corresponding to the standardized index data. The formula for the calculation of the entropy weight can be as follows:
wherein the content of the first and second substances,
representing entropy weights, i.e. objective weights, (1-e) j ) Representing entropy redundancy. The entropy weight is positively correlated with the entropy redundancy, namely: the larger the redundancy of the entropy value is, the more information the index contains, and the entropy weight is increased.
Further, in the process of calculating the objective weight by using the entropy weight method, normalization processing needs to be performed first. Since the normalized index data in this embodiment can be obtained by normalizing the evaluation index data according to the above formula (2), the normalization method adopted by the entropy weight method in this embodiment is different from the conventional method. The normalization processing mode has the advantage that whether the single power quality evaluation index exceeds the standard can be directly judged. When the normalization result is more than 1, the power quality evaluation index exceeds the standard, and the unqualified power quality of the area to be evaluated can be directly judged. And if the normalization result is less than or equal to 1, indicating that the power quality evaluation index does not exceed the standard, and performing power quality evaluation according to the power quality evaluation method.
After the subjective weight and the objective weight are obtained, the server combines the subjective weight and the objective weight according to a preset weight relation, and calculates a combined index weight corresponding to the standardized index data. The conventional calculation formula of the combined index weight is as follows:
wherein, ω is j Represents the combined index weight, omega, corresponding to the normalized index data 1j The subjective weight, omega, of the jth power quality assessment index corresponding to the standardized index data 2j And representing the objective weight of the jth power quality assessment index corresponding to the standardized index data.
When the subjective weight or the objective weight of a certain power quality assessment index is higher, the combined weighting method shown in the above formula can amplify the influence of the power quality assessment index on the power quality assessment result to a greater extent, which may cause unreasonable weight distribution. Thus, with slight modifications to the above formula, an improved combinatorial weighting method is as follows:
wherein, ω is j Represents the combined index weight, omega, corresponding to the normalized index data 1j The subjective weight, omega, of the jth power quality assessment index corresponding to the standardized index data 2j And representing the objective weight of the jth power quality assessment index corresponding to the standardized index data.
In one embodiment, obtaining a pre-constructed power quality assessment system corresponding to a region to be assessed includes: acquiring monitoring data of a plurality of monitoring points in an area to be evaluated; determining power quality evaluation indexes according to the monitoring data of the monitoring points and the key load types corresponding to the monitoring points; and constructing a power quality evaluation system corresponding to the area to be evaluated according to the power quality evaluation index.
The server can obtain all monitoring data of a plurality of monitoring points in the area to be evaluated and the key load types corresponding to the monitoring points. The monitoring data can be all state data corresponding to the power quality monitoring point and related to the power quality, including voltage flicker, voltage deviation, inter-harmonic, voltage fluctuation, frequency deviation and the like. The critical load types corresponding to the monitoring points may include photovoltaic power stations, wind turbines, electric arc furnaces, and electrified railways. Therefore, an evaluation system is constructed according to the monitoring data and the key load type. Specifically, the server may select the power quality assessment index according to the monitoring data and the key load type. Further, the selection of the power quality evaluation index should meet the following requirements:
1. all-round
The power quality evaluation index in the evaluation system can comprehensively and accurately reflect the power quality condition of the area to be evaluated, and the selected index needs to cover various power quality problems possibly occurring in the area to be evaluated as much as possible. For example, for the load of the arc furnace, the dominant harmonic is 2-7 times, so that the current content of the harmonic of 2-7 times can be brought into an evaluation system to more comprehensively reflect the harmonic characteristics of the arc furnace.
2. Simplicity of operation
The more the number of the electric energy quality evaluation indexes in the evaluation system is, the better the electric energy quality evaluation indexes are, information redundancy should be avoided, so that the calculation amount is reduced, and the evaluation efficiency is improved. If the frequency automatic control technology in China is mature, the frequency is usually kept at a level very close to 50Hz, so that the index of frequency deviation can be ignored.
3. Uniformity of use
The power grid of the area to be evaluated is provided with a plurality of monitoring points, and in order to realize horizontal and longitudinal evaluation of the power grid of the area, the conditions of the monitoring points are comprehensively considered, and a uniform evaluation system suitable for the monitoring points is constructed.
In the embodiment, the load interference characteristic is fully considered, and after investigation and research are carried out on the loads of all monitoring points of the regional power grid, the regional power grid mainly has four types of loads, namely a photovoltaic power station, a fan, an electric arc furnace and an electrified railway. Since there is usually no inter-harmonic and voltage fluctuation information in the power quality transient indicators, these indicators are not included in the evaluation system of the present invention. The harmonics of order 2, 3, 4, 6 of the load, such as an arc furnace, are also significant and are taken into account in the evaluation system. And after comprehensively considering the comprehensiveness, simplicity and uniformity of the indexes, constructing an evaluation system.
In this embodiment, an electric energy quality evaluation index is determined according to monitoring data of a plurality of monitoring points and a key load type corresponding to each monitoring point, and an evaluation system corresponding to an area to be evaluated is constructed according to the electric energy quality evaluation index. The power quality assessment index is determined according to all monitoring data and the key load types of all monitoring points, so that the power quality assessment index can comprehensively and accurately reflect the power quality condition of the area to be assessed and can cover various power quality problems which may occur in the area to be assessed, and therefore the comprehensiveness and accuracy of power quality assessment are improved.
In another embodiment, as shown in fig. 5, there is provided a power quality assessment method, including the steps of:
And step 504, determining the power quality evaluation index.
And determining the power quality evaluation index according to the monitoring data of the monitoring points and the key load types corresponding to the monitoring points.
And establishing an evaluation system corresponding to the area to be evaluated according to the power quality evaluation index.
And step 508, obtaining evaluation index data.
And obtaining the evaluation index data of a plurality of monitoring points in the area to be evaluated according to the evaluation system.
And step 510, normalization processing.
And carrying out normalization processing on the evaluation index data to obtain standardized index data.
And carrying out hierarchical analysis processing on the power quality evaluation indexes corresponding to the standardized index data to obtain subjective weights corresponding to the standardized index data.
And performing entropy weight calculation on the standardized index data to obtain objective weight corresponding to the standardized index data.
In step 516, the combined index weight is calculated.
And calculating the combined index weight corresponding to the standardized index data according to the subjective weight, the objective weight and the preset weight relation.
And 518, calculating an average solution reference value of each power quality evaluation index.
And calculating the average solution reference value of each power quality evaluation index corresponding to the standardized index data according to a preset calculation relation.
And calculating the ideal solution distance of the standardized index data according to the preset calculation relation and the average solution reference value.
At step 522, distance weighting sum data corresponding to each monitoring point is calculated.
And weighting and calculating the ideal solution distance of the standardized index data corresponding to each monitoring point according to the preset calculation relationship and the combined index weight to obtain distance weighted sum data corresponding to each monitoring point.
And carrying out standardization processing on the distance weighted sum data to obtain distance weighted sum standard data.
And carrying out mean value calculation on the distance weighting and the standard data to obtain the electric energy quality evaluation result of the area to be evaluated.
In the power quality assessment method, the power quality assessment index is determined according to all monitoring data and the key load types of all monitoring points, so that the power quality assessment index can comprehensively and accurately reflect the power quality condition of the area to be assessed and can cover various power quality problems which may occur in the area to be assessed, and the comprehensiveness and the accuracy of power quality assessment are improved. The combined index weight of each power quality index is determined by adopting a subjective and objective combined weighting method, so that the evaluation index data of each monitoring point is objectively and reasonably evaluated, the time complexity of the power quality evaluation process is reduced, and the influence of artificial subjective factors is reduced as much as possible. Meanwhile, the power quality grades of all monitoring points can be obtained, the power quality ranking of all monitoring points can be obtained, and the continuously-increased power price making requirement of the power distribution network and the high requirement for power quality evaluation are met.
The power quality evaluation method is described below by taking power grid data of a certain area as an example. The regional power grid is provided with 20 online power quality monitoring points, the voltage level coverage range of the monitoring points is 10V-220 kV, and 10 substations above 110kV are involved. The monitoring user types, namely the load types, mainly comprise photovoltaic power stations (4), fans (4), electrified railways (4) and electric arc furnaces (8), and the information of each monitoring point can be shown in the following table:
TABLE 3 information of monitoring points
Taking the evaluation index data of each monitoring point in january of the area as an example. The normalized index data for january is shown in the following table:
TABLE 4 standardized index data
| Monitoring point/index type | ΔU | P It | ξ U | THD U | HRI 2 | HRI 3 | HRI 4 | HRI 5 | HRI 6 | HRI 7 | HRI 11 | HRI 13 |
| 1 | 1.450 | 0.446 | 0.891 | 0.476 | 0.465 | 0.311 | 0.846 | 0.965 | 0.345 | 0.909 | 0.844 | 0.735 |
| 2 | 0.815 | 0.646 | 1.066 | 1.219 | 1.012 | 2.177 | 1.605 | 2.458 | 0.422 | 0.845 | 0.965 | 1.732 |
| 3 | 0.679 | 0.797 | 0.547 | 1.562 | 1.672 | 2.614 | 2.258 | 2.256 | 0.452 | 0.791 | 1.326 | 1.763 |
| 4 | 0.758 | 2.630 | 0.439 | 0.948 | 0.556 | 0.811 | 0.436 | 0.730 | 0.565 | 0.489 | 0.495 | 0.379 |
| 5 | 0.743 | 0.506 | 0.418 | 0.586 | 0.794 | 0.731 | 0.769 | 1.912 | 0.811 | 0.338 | 0.649 | 0.533 |
| 6 | 0.392 | 0.699 | 0.358 | 0.757 | 0.485 | 0.779 | 0.438 | 0.560 | 0.374 | 0.800 | 0.732 | 2.525 |
| 7 | 0.655 | 1.932 | 0.841 | 0.654 | 0.457 | 0.834 | 0.389 | 0.800 | 0.428 | 0.369 | 0.648 | 0.351 |
| 8 | 0.471 | 0.709 | 0.754 | 0.587 | 0.346 | 0.569 | 0.548 | 0.431 | 0.517 | 1.010 | 0.451 | 0.550 |
| 9 | 0.706 | 0.755 | 0.814 | 0.568 | 0.632 | 0.869 | 0.673 | 0.931 | 0.661 | 0.876 | 0.622 | 0.587 |
| 10 | 0.277 | 0.676 | 0.644 | 0.612 | 0.456 | 0.637 | 0.456 | 0.821 | 0.820 | 0.508 | 0.501 | 0.471 |
| 11 | 0.823 | 0.680 | 0.629 | 0.794 | 0.679 | 0.602 | 0.765 | 20.548 | 0.755 | 2.684 | 2.484 | 1.343 |
| 12 | 0.695 | 0.655 | 0.450 | 0.311 | 0.591 | 0.763 | 0.749 | 0.869 | 0.657 | 0.780 | 0.547 | 0.430 |
| 13 | 0.317 | 0.563 | 0.497 | 0.529 | 0.722 | 0.654 | 0.833 | 0.758 | 0.732 | 0.390 | 0.496 | 0.687 |
| 14 | 1.041 | 0.619 | 0.651 | 0.759 | 0.679 | 0.689 | 0.690 | 0.755 | 0.801 | 0.642 | 0.745 | 0.668 |
| 15 | 0.340 | 0.698 | 0.616 | 0.913 | 0.633 | 0.748 | 0.532 | 0.853 | 0.596 | 0.404 | 0.589 | 0.626 |
| 16 | 0.439 | 1.069 | 0.473 | 0.826 | 0.712 | 0.851 | 0.711 | 0.622 | 0.771 | 0.575 | 0.487 | 0.780 |
| 17 | 0.382 | 0.340 | 0.752 | 0.538 | 0.398 | 0.817 | 0.574 | 0.751 | 0.533 | 0.435 | 0.436 | 0.729 |
| 18 | 0.766 | 0.585 | 0.831 | 1.171 | 0.448 | 0.869 | 0.645 | 0.513 | 0.321 | 0.353 | 0.447 | 0.776 |
| 19 | 0.795 | 0.224 | 0.585 | 0.443 | 0.535 | 0.400 | 0.586 | 0.511 | 0.442 | 0.818 | 1.847 | 0.795 |
| 20 | 0.490 | 0.751 | 0.550 | 0.402 | 0.431 | 0.509 | 0.604 | 0.644 | 0.500 | 0.812 | 2.047 | 1.748 |
The method comprises the following steps of taking 'power quality' as a target layer, forming an index layer by all power quality evaluation indexes in an evaluation system, inviting a plurality of experts in the power quality field to score all the power quality evaluation indexes, and obtaining a scoring table which can be as follows:
TABLE 5 scoring table
| Index (I) | ΔU | P It | ξ U | THD U | I 2 | I 3 | I 4 | I 5 | I 6 | I 7 | I 11 | I 13 |
| ΔU | 1 | 1/2 | 1/2 | 1/3 | 3 | 2 | 5 | 2 | 5 | 2 | 2 | 2 |
| P It | 2 | 1 | 1 | 1/2 | 5 | 3 | 7 | 3 | 7 | 3 | 3 | 3 |
| ξ U | 2 | 1 | 1 | 1/2 | 5 | 3 | 7 | 3 | 7 | 3 | 3 | 3 |
| THD U | 3 | 2 | 2 | 1 | 7 | 5 | 9 | 5 | 9 | 5 | 4 | 4 |
| I 2 | 1/3 | 1/5 | 1/5 | 1/7 | 1 | 1/2 | 2 | 1/2 | 2 | 1/2 | 1/3 | 1/3 |
| I 3 | 1/2 | 1/3 | 1/3 | 1/5 | 2 | 1 | 3 | 1 | 3 | 1 | 1/2 | 1/2 |
| I 4 | 1/5 | 1/7 | 1/7 | 1/9 | 1/2 | 1/3 | 1 | 1/3 | 1 | 1/3 | 1/4 | 1/4 |
| I 5 | 1/2 | 1/3 | 1/3 | 1/5 | 2 | 1 | 3 | 1 | 3 | 1 | 1/2 | 1/2 |
| I 6 | 1/5 | 1/7 | 1/7 | 1/9 | 1/2 | 1/3 | 1 | 1/3 | 1 | 1/3 | 1/4 | 1/4 |
| I 7 | 1/2 | 1/3 | 1/3 | 1/5 | 2 | 1 | 3 | 1 | 3 | 1 | 1/2 | 1/2 |
| I 11 | 1/2 | 1/3 | 1/3 | 1/4 | 3 | 2 | 4 | 2 | 4 | 2 | 1 | 1 |
| I 13 | 1/2 | 1/3 | 1/3 | 1/4 | 3 | 2 | 4 | 2 | 4 | 2 | 1 | 1 |
The maximum eigenvalue of the decision matrix formed in the above table is λ max 12.209, the corresponding largest feature vector is:
ξ max ＝(0.262，0.420，0.420，0.663，0.078，0.130，0.050，0.130，0.050，0.130，0.195，0.195)
and (3) carrying out normalization processing on the maximum feature vector:
ξ' max ＝(0.096，0.154，0.154，0.243，0.029，0.048，0.018，0.048，0.018，0.048，0.072，0.072)
after averaging the normalized vectors, the subjective weight is obtained as follows:
ω AHP ＝(0.100，0.152，0.161，0.233，0.029，0.056，0.020，0.042，0.022，0.049，0.071，0.065)
and calculating the objective weight of each power quality assessment index by an entropy weight method, substituting the subjective weight and the objective weight into the formula (13), and calculating to obtain the combined index weight of each power quality assessment index. And (3) comprehensively evaluating the combined index weight and the standardized index data by using an EDAS algorithm and using the formulas (3), (4) and (6) - (8) to obtain the electric energy quality evaluation result of the area to be evaluated. The evaluation data of some monitoring points in the power quality evaluation result can be shown in the following table:
meter 6 electric energy quality evaluation result
It should be understood that, although the steps in the flowcharts related to the embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides a power quality evaluation device for realizing the power quality evaluation method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so the specific limitations in one or more embodiments of the power quality assessment device provided below can be referred to the limitations on the power quality assessment method in the foregoing, and details are not repeated here.
In one embodiment, as shown in fig. 6, there is provided a power quality evaluation apparatus including: an evaluation system obtaining module 602, an index data obtaining module 604, a normalization processing module 606, a combined empowerment calculating module 608, and an electric energy quality evaluating module 610, wherein:
an evaluation system obtaining module 602, configured to obtain a pre-constructed power quality evaluation system corresponding to the area to be evaluated.
The index data obtaining module 604 is configured to obtain evaluation index data of multiple monitoring points in the area to be evaluated according to the power quality evaluation system.
And a normalization processing module 606, configured to perform normalization processing on the evaluation index data to obtain normalized index data.
And a combined weighting calculation module 608, configured to perform combined weighting calculation on the normalized index data to obtain a combined index weight corresponding to the normalized index data.
And the power quality evaluation module 610 is configured to perform comprehensive evaluation on the combined index weight and the standardized index data to obtain a power quality evaluation result of the area to be evaluated.
In one embodiment, the power quality assessment module 610 is further configured to calculate distance weighting sum data corresponding to each monitoring point according to the combined index weight, the standardized index data, and a preset calculation relationship; standardizing the distance weighted sum data to obtain distance weighted sum standard data; and carrying out mean value calculation on the distance weighting and the standard data to obtain the electric energy quality evaluation result of the area to be evaluated.
In one embodiment, the power quality assessment module 610 is further configured to calculate an average solution reference value of each power quality assessment indicator corresponding to the normalized indicator data according to a preset calculation relationship; calculating an ideal solution distance of the standardized index data according to a preset calculation relation and the average solution reference value; and weighting and calculating the ideal solution distance of the standardized index data corresponding to each monitoring point according to the preset calculation relationship and the combined index weight to obtain distance weighted sum data corresponding to each monitoring point.
In an embodiment, the combined weighting calculation module 608 is further configured to perform hierarchical analysis processing on the power quality assessment indicators corresponding to the standardized indicator data to obtain subjective weights corresponding to the standardized indicator data; performing entropy weight calculation on the standardized index data to obtain objective weight corresponding to the standardized index data; and calculating the combined index weight corresponding to the standardized index data according to the subjective weight, the objective weight and the preset weight relation.
In one embodiment, the normalization processing module 606 is further configured to perform ratio calculation on the evaluation index data and the corresponding preset index threshold; and determining the calculated ratio as the standard index data.
In an embodiment, the evaluation system obtaining module 602 is further configured to obtain monitoring data of a plurality of monitoring points in the area to be evaluated; determining power quality evaluation indexes according to the monitoring data of the monitoring points and the key load types corresponding to the monitoring points; and constructing a power quality evaluation system corresponding to the area to be evaluated according to the power quality evaluation index.
All or part of each module in the power quality evaluation device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, an Input/Output interface (I/O for short), and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing data such as an electric energy quality evaluation system, evaluation index data, electric energy quality evaluation results and the like. The input/output interface of the computer device is used for exchanging information between the processor and an external device. The communication interface of the computer device is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a power quality assessment method.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, carries out the steps in the method embodiments described above.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the relevant laws and regulations and standards of the relevant country and region.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. A method for assessing power quality, the method comprising:
acquiring a pre-constructed power quality evaluation system corresponding to a region to be evaluated;
obtaining evaluation index data of a plurality of monitoring points in the area to be evaluated according to the power quality evaluation system;
normalizing the evaluation index data to obtain standardized index data;
performing combined weighting calculation on the standardized index data to obtain a combined index weight corresponding to the standardized index data;
and comprehensively evaluating the combined index weight and the standardized index data to obtain an electric energy quality evaluation result of the area to be evaluated.
2. The method according to claim 1, wherein the comprehensively evaluating the combined index weight and the standardized index data to obtain the power quality evaluation result of the area to be evaluated comprises:
calculating distance weighting sum data corresponding to each monitoring point according to the combined index weight, the standardized index data and a preset calculation relation;
carrying out standardization processing on the distance weighted sum data to obtain distance weighted sum standard data;
and carrying out mean value calculation on the distance weighting and the standard data to obtain the electric energy quality evaluation result of the area to be evaluated.
3. The method of claim 2, wherein calculating distance weighted sum data corresponding to each monitoring point according to the combined indicator weight, the normalized indicator data and a preset calculation relationship comprises:
calculating an average solution reference value of each power quality evaluation index corresponding to the standardized index data according to a preset calculation relation;
calculating an ideal solution distance of the standardized index data according to the preset calculation relation and the average solution reference value;
and weighting and calculating the ideal solution distance of the standardized index data corresponding to each monitoring point according to the preset calculation relationship and the combined index weight to obtain distance weighted sum data corresponding to each monitoring point.
4. The method according to claim 1, wherein the performing a combined weighting calculation on the normalized index data to obtain a combined index weight corresponding to the normalized index data comprises:
performing hierarchical analysis processing on the power quality assessment indexes corresponding to the standardized index data to obtain subjective weights corresponding to the standardized index data;
performing entropy weight calculation on the standardized index data to obtain objective weight corresponding to the standardized index data;
and calculating the combined index weight corresponding to the standardized index data according to the subjective weight, the objective weight and a preset weight relation.
5. The method of claim 1, wherein the normalizing the evaluation index data to obtain normalized index data comprises:
calculating the ratio of the evaluation index data to a corresponding preset index threshold;
and determining the calculated ratio as the standard index data.
6. The method according to any one of claims 1 to 5, wherein the obtaining of the pre-constructed power quality assessment system corresponding to the area to be assessed comprises:
acquiring monitoring data of a plurality of monitoring points in an area to be evaluated;
determining power quality evaluation indexes according to the monitoring data of the monitoring points and the key load types corresponding to the monitoring points;
and constructing a power quality evaluation system corresponding to the area to be evaluated according to the power quality evaluation index.
7. An electric energy quality evaluation apparatus, characterized in that the apparatus comprises:
the evaluation system acquisition module is used for acquiring a pre-constructed electric energy quality evaluation system corresponding to the area to be evaluated;
the index data acquisition module is used for acquiring the evaluation index data of a plurality of monitoring points in the area to be evaluated according to the power quality evaluation system;
the normalization processing module is used for performing normalization processing on the evaluation index data to obtain normalized index data;
the combined weighting calculation module is used for performing combined weighting calculation on the standardized index data to obtain a combined index weight corresponding to the standardized index data;
and the electric energy quality evaluation module is used for comprehensively evaluating the combined index weight and the standardized index data to obtain an electric energy quality evaluation result of the area to be evaluated.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757717A (en) * | 2023-05-19 | 2023-09-15 | 南方电网能源发展研究院有限责任公司 | Method, device, equipment, medium and product for evaluating electric carbon market coupling operation |
| CN117422195A (en) * | 2023-10-08 | 2024-01-19 | 曙光云计算集团有限公司 | Water quality evaluation method, device, computer equipment and storage medium |
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2022
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757717A (en) * | 2023-05-19 | 2023-09-15 | 南方电网能源发展研究院有限责任公司 | Method, device, equipment, medium and product for evaluating electric carbon market coupling operation |
| CN117422195A (en) * | 2023-10-08 | 2024-01-19 | 曙光云计算集团有限公司 | Water quality evaluation method, device, computer equipment and storage medium |
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