CN117932367A - Evaluation index screening method and system for wind-solar-energy-storage integrated operation system - Google Patents
Evaluation index screening method and system for wind-solar-energy-storage integrated operation system Download PDFInfo
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Abstract
The invention discloses an evaluation index screening method and system of a wind-solar-energy-storage integrated operation system, and belongs to the technical field of wind-solar-energy-storage system analysis. According to the invention, firstly, the index is subjected to dimension reduction by a method of combining cluster analysis and AHP (hierarchical analysis), the index is subjected to cluster analysis preliminarily, the index with high correlation is clustered into one type, then the index with the largest weight is screened out by adopting the AHP method and used as a representative index of one type of index, the KMO coefficient is used for judging the overlapping degree of various representative indexes, and the index with overlapping property is deleted according to the sampling suitability of each representative index, so that the information overlapping property among indexes is reduced, and the accuracy of comprehensive evaluation of system benefit is improved.
Description
Technical Field
The invention relates to the technical field of wind and light storage system analysis, in particular to an evaluation index screening method and system of a wind and light storage integrated operation system.
Background
The wind-solar-energy-storage integrated system is a complex with multiple indexes, and if the system is required to be subjected to multi-dimensional benefit comprehensive evaluation, whether the screened evaluation indexes are accurate and reasonable directly influence the final evaluation result. The wind-solar-energy-storage integrated operation multidimensional benefit evaluation index system needs to have comprehensiveness, but the redundancy and overlapping of indexes are inevitably generated, the complexity of analysis and calculation is increased, and the accuracy of a final evaluation result is affected. Therefore, the screening of proper and reasonable indexes from a plurality of evaluation indexes becomes a key influencing factor for the evaluation of the system benefit.
The current common methods for research on index screening can be divided into subjective analysis methods, objective analysis methods and subjective and objective combination methods. Typical among subjective analysis methods are theoretical analysis and expert consultation, but these methods are too subjective, resulting in one-sided results; the methods commonly used in objective analysis include principal component analysis, factor analysis, and cluster analysis, but such methods require a large amount of index sample data.
In the current research on index screening, in solving the redundancy problem of indexes, most of adopted factor analysis methods delete redundant indexes through factor load or contribution rate of the indexes, but the method can delete indexes with obvious influence on evaluation results by mistake, the deleted indexes have great influence on the sorting of the evaluation results, and the method also has no function of weighting the indexes.
In solving the problem of overlapping of indexes, most of the adopted methods adopt a principal component analysis method, a characteristic extraction method and the like, and along with screening of evaluation indexes, the objective evaluation of the level of an evaluated object is taken as a target, so that the dimension reduction of the evaluation indexes cannot simply refer to the existing dimension reduction method.
Therefore, the method and the system for screening the evaluation indexes of the wind-solar-energy-storage integrated operation system are provided, the indexes without redundancy and overlapping performance are screened from a large number of original indexes, and the effectiveness and the accuracy of the evaluation indexes are improved, so that the problem to be solved by the person skilled in the art is urgent.
Disclosure of Invention
In view of the above, the invention provides an evaluation index screening method and an evaluation index screening system for a wind-solar-energy-storage integrated operation system.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
on the one hand, the invention discloses an evaluation index screening method of a wind-solar-energy-storage integrated operation system, which comprises the following steps:
s1, establishing a wind-solar-energy-storage integrated operation multidimensional benefit evaluation system, and acquiring an initial evaluation index;
s2, classifying the initial evaluation index based on cluster analysis;
S3, calculating the weight of each type of index by adopting an analytic hierarchy process, and selecting the index with the largest weight in each type of index as a representative index;
s4, calculating the KMO coefficient of the representative index;
s5, judging whether an overlapping index exists according to the KMO coefficient; if the representative index does not exist, the representative index is used as a final evaluation index; if the sample suitability quantity of the representative index exists, determining the overlapping index, and deleting the overlapping index;
S6, repeating S4-S5 aiming at the representative index after deleting the overlapped index until the overlapped index does not exist, and stopping screening, wherein the rest representative index is a final evaluation index.
Preferably, the S2 includes:
Carrying out standardization treatment on the initial evaluation index to obtain a standardization index;
calculating a correlation coefficient between evaluation indexes based on the standardized indexes;
and merging the indexes of which the correlation coefficients are close to the first preset value into one type of indexes, wherein the indexes of which the correlation coefficients are close to the second preset value are independently used as one type of indexes.
Preferably, the S3 includes:
Constructing a judging matrix of a certain type of indexes;
Consistency test is carried out on the judgment matrix, and the maximum characteristic root and the corresponding characteristic vector of the judgment matrix are solved;
Calculating index weight according to the maximum feature root and the corresponding feature vector of the judgment matrix;
And selecting the index with the largest weight as a representative index of the index.
Preferably, in S5, determining whether there is an overlap indicator according to the KMO coefficient includes:
Judging whether the KMO coefficient is smaller than a KMO threshold, if so, not existence of the overlapped index, otherwise, existence of the overlapped index.
Preferably, determining the overlap indicator according to the sampling suitability amount of the representative indicator in S5 includes:
Calculating the sampling suitability quantity of each representative index respectively;
And taking the representative index with the largest sampling suitability quantity as the overlapping index.
On the other hand, the invention also discloses an evaluation index screening system of the wind-solar-energy-storage integrated operation system, which is used for realizing the method and comprises the following steps:
The evaluation system construction module is used for establishing a wind-solar-energy-storage integrated operation multidimensional benefit evaluation system and acquiring initial evaluation indexes;
The clustering module is used for classifying the initial evaluation indexes based on cluster analysis;
The representative index acquisition module is used for calculating the weight of each type of index by adopting an analytic hierarchy process and selecting the index with the largest weight in each type of index as the representative index;
A KMO calculation module, configured to calculate KMO coefficients of the representative index;
The overlapping index judging module is used for judging whether an overlapping index exists according to the KMO coefficient;
and the output module is used for acquiring the final evaluation index according to the judgment result of the overlapping index.
Preferably, the clustering module includes:
the standardized processing unit is used for carrying out standardized processing on the initial evaluation index to obtain a standardized index;
A correlation coefficient calculation unit for calculating a correlation coefficient between the evaluation indexes based on the standardized indexes;
And the index classification unit is used for combining the indexes of which the correlation coefficients are close to the first preset value into one type of indexes, and the indexes of which the correlation coefficients are close to the second preset value are independently used as one type of indexes.
Preferably, the representative index obtaining module includes:
the judging matrix construction unit is used for constructing a judging matrix of a certain type of indexes;
The consistency checking unit is used for carrying out consistency checking on the judgment matrix and solving the maximum characteristic root and the corresponding characteristic vector of the judgment matrix;
the weight calculation unit is used for calculating index weight according to the maximum characteristic root of the judgment matrix and the corresponding characteristic vector;
The representative index selecting unit is used for selecting the index with the largest weight as the representative index of the index.
Preferably, the output module includes:
An overlapping index processing unit, configured to determine an overlapping index according to the sampling suitability amount of the representative index when the overlapping index exists, and delete the overlapping index;
And the final evaluation index output unit is used for acquiring the final evaluation index according to the judgment result of the overlapping index.
Compared with the prior art, the invention discloses an evaluation index screening method and an evaluation index screening system for a wind-solar-energy-storage integrated operation system, wherein the method comprises the steps of firstly reducing the dimensions of indexes by a method combining cluster analysis and AHP (hierarchical analysis), primarily clustering the indexes, clustering the indexes with high correlation into one type, screening out the index with the maximum weight by adopting the AHP method as a representative index of the one type of indexes, judging the overlapping degree among various representative indexes by utilizing a KMO coefficient, deleting the index with the overlapping property according to the sampling suitability quantity (namely KMa i coefficient) of each representative index, further reducing the information overlapping property among the indexes, and improving the accuracy of comprehensive evaluation of the system benefit.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a cluster tree diagram of low-carbon benefit evaluation indexes provided by the embodiment of the invention;
Fig. 3 is a system architecture diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The screening of the evaluation indexes in the embodiment of the invention aims at a novel wind-light-storage comprehensive power generation system which integrates two novel energy storage modes of solid-state heat storage and hydrogen storage on the basis of wind-light-storage integration, namely wind power generation, photovoltaic power generation and battery energy storage.
The embodiment of the invention discloses an evaluation index screening method of a wind-solar-energy-storage integrated operation system, which comprises the following steps of:
s1, establishing a wind-solar-energy-storage integrated operation multidimensional benefit evaluation system, and obtaining an initial evaluation index.
According to the wind-solar energy-storage integrated operation characteristics and the theoretical basis of a comprehensive benefit evaluation index system, introducing a full life cycle theory, constructing a wind-solar energy-storage integrated operation multidimensional benefit evaluation system from five dimensions of an energy efficiency benefit index, an economic benefit index, a social benefit index, a low-carbon benefit index and an enterprise development benefit, and acquiring initial evaluation indexes in each dimension, wherein the method comprises the following steps of:
(1) Initial evaluation index of energy efficiency benefit:
The energy efficiency evaluation index is mainly used for evaluating the application of the wind-solar energy storage integrated system in the power grid side in the aspect of self performance, and the wind-solar energy storage and equipment energy efficiency indexes of different manufacturers and different models can be selected to generate a certain degree of influence. And selecting power density, electric energy quality, energy efficiency grade, integrated operation prediction capability, schedulability and the like as initial evaluation indexes of energy efficiency benefits.
(2) Initial evaluation index of economic benefit:
The economic evaluation index is a starting point of the engineering economic benefit of the wind-solar-energy-storage integrated operation system. The development and operation of the wind-solar-energy-storage integrated operation system project bring cost and benefit to the receiving-end power grid from the perspective of cost and benefit. The cost mainly comprises: initial investment costs and operational maintenance costs. The economic benefit mainly comes from the direct benefit of wind-solar energy storage integrated operation and the peak-valley electricity price difference obtained by participating in the peak regulation of the electric power market; and the benefits of reducing the power grid loss caused by integrated operation and the like.
(3) Initial evaluation index of social benefit:
When the wind-solar-energy-storage integrated operation system is applied to a receiving-end power grid, direct economic benefits can be brought to the power grid, the wind-solar-storage integrated operation system can be used as a standby power supply to improve the power supply reliability of the power grid, smooth clean energy output and participate in frequency modulation to improve the power supply quality, and the continuity and reliability contribution rate of power supply are ensured to be the social index research content.
(4) Initial evaluation index of low carbon benefit:
The low-carbon benefit (environment) evaluation index is an index for measuring the importance of the wind-solar-energy-storage integrated operation system in promoting the power grid upgrading and energy transformation. Currently, the development of clean energy to replace traditional energy is slow. Based on sustainable development theory, wind-solar energy storage integrated development is a key technology for improving clean energy consumption rate, reducing carbon emission and realizing large-scale replacement of clean energy. Therefore, the low-carbon benefit (environment) evaluation index comprises a new energy consumption change value, energy saving and emission reduction benefits and the like.
(5) Initial evaluation index of enterprise development benefit:
the enterprise development benefit evaluation index is a key index for measuring the development condition of the enterprise and supporting the operation efficiency and the resource allocation efficiency of wind-solar energy storage integration. The initial evaluation index of the enterprise development benefit comprises enterprise operation benefit, asset allocation benefit, investment benefit, profit level and the like.
S2, classifying initial evaluation indexes based on cluster analysis, wherein the method specifically comprises the following steps:
s21, carrying out standardization treatment on the initial evaluation index to obtain a standardization index.
N initial evaluation index variables are o 1,o2,o3,...,on respectively, and after standardized treatment, all initial evaluation indexes o i are converted into standardized indexesThe formula is as follows:
wherein, The sample mean value of the initial evaluation index; s i is the sample standard deviation of the initial evaluation index.
S22, calculating a correlation coefficient between the initial evaluation indexes based on the standardized indexes.
In this embodiment, a simple correlation coefficient method is used to measure the correlation between the initial evaluation indexes of each dimension, and the formula is as follows:
where ρ ij represents simple correlation coefficients of the initial evaluation indexes o i and o j (i=1, 2,3,., n; j=1, 2,3, n), representing the degree of overlap between the initial evaluation indexes.
S23, merging indexes with correlation coefficients close to a first preset value into one type of indexes, wherein the indexes with the correlation coefficients close to a second preset value are independently used as one type of indexes, specifically, the first preset value is 1 or-1, and the second preset value is 0.
The correlation coefficient is close to 1 or-1, and the correlation between indexes is high; a correlation coefficient of 0 indicates no correlation between the indices.
S3, calculating the weight of each type of index by adopting an analytic hierarchy process, selecting the index with the largest weight in each type of index as a representative index, and deleting the rest indexes, wherein the method comprises the following steps:
S31, constructing a judgment matrix of a certain type of indexes;
And comparing the indexes of the first layer in pairs to form a judgment matrix. (U ij)n×n (i=1 to n, j=1 to n) represents a value of the relative importance degree comparison between the elements, and a judgment matrix formed by the comparison results is as follows:
u ij is an element of the judgment matrix U.
The comparison principle is a nine-bit scale as shown in table 1.
Table 1 nine-digit scale
S32, consistency test is conducted on the judgment matrix, and the maximum characteristic root and the corresponding characteristic vector of the judgment matrix are solved.
After the judgment matrix is constructed, consistency test is performed on the judgment matrix. The analytic hierarchy process converts subjective judgment of people into objective description as much as possible, gradually screens out the principals, and expresses and processes the subjective judgment of people in a formalized mode. The reasonable degree of proportion of the objective component directly affects the correctness and success thereof. Judging the consistency of the matrix is important in the AHP method, and directly influences the objective ordering among indexes. And judging whether the consistency of the judgment matrix is satisfactory or not through consistency indexes, introducing a consistency check index CI, and finally solving the problem of the maximum characteristics and the characteristic vectors of the judgment matrix.
CI＝(λmax-n)/(n-1)
Lambda max is the maximum feature root of the judgment matrix, the calculated CI value is compared with the corresponding value of the average random consistency index RI, and the consistency ratio is introduced, wherein the formula is as follows:
CR＝CI/RI；
when CR <0.1, the judgment matrix has satisfactory consistency.
S33, calculating index weight according to the maximum characteristic root lambda max of the judgment matrix and the corresponding characteristic vector W.
The method for calculating the maximum feature root lambda max of the judgment matrix and the corresponding feature vector W comprises the following steps:
M i is the product of each row of elements of the judgment matrix;
the n-th root of M i is calculated,
Vector pairNormalizing, wherein the index weight w i is as follows:
S34, selecting the index with the largest weight as a representative index of the index.
S4, calculating KMO coefficients of the representative indexes, wherein the calculation formula is as follows:
Wherein r ij represents the simple correlation coefficients of the representative indexes x i and x j; Representing the partial correlation coefficients of the representative indexes x i and x j,/> P ij is the corresponding element of the inverse of the correlation coefficient matrix.
S5, judging whether an overlapping index exists according to the KMO coefficient, specifically judging whether the KMO coefficient is smaller than a KMO threshold, setting the KMO threshold to be 0.7, if the KMO coefficient is smaller than 0.7, the overlapping index does not exist, and directly taking the representative index as a final evaluation index; otherwise, an overlap indicator exists.
When the overlapping index exists, determining the overlapping index according to the sampling suitability quantity of the representative index, and deleting the overlapping index, wherein the method comprises the following steps of:
S51, respectively calculating the sampling suitability quantity of each representative index, namely KMa i values, wherein the calculation formula is as follows:
S52, taking the representative index with the largest sampling suitability as an overlapping index, and deleting.
If the calculated result KMa i is close to 1, the correlation between the representative index and other representative indexes is strong, and the representative index is deleted; otherwise, KMa i values close to 0 indicate that the correlation between the representative index and other representative indexes is weak, and the value is reserved.
S6, repeating S4-S5 aiming at the representative indexes with the overlapped indexes deleted until the overlapped indexes are not existed, and stopping screening, wherein the rest representative indexes are final evaluation indexes.
In an alternative embodiment of the present invention, the method for verifying the present invention by selecting the low carbon benefit index in five dimensions comprises the following specific steps:
s1, selecting an initial low-carbon benefit evaluation index as shown in table 2. The data are derived from the data of a wind-solar-energy-storage integrated operation system of a power company in Jilin province and the data of other power companies.
TABLE 2 initial Low carbon Effect evaluation index
S2, after clustering calculation, the low-carbon benefit initial evaluation index clustering tree is shown in fig. 2, wherein the ordinate in fig. 2 is a clustering target variable, the abscissa refers to the relative distance of the classes, the change condition of the distances between the classes is represented, and the size of the distance represents the size of the characteristics of the classes. In the figure, 16 represents U416 in the initial low carbon benefit evaluation index of Table 2 above, and so on.
After the clustering is completed, the original 20 low-carbon benefit initial evaluation indexes are clustered into 11 types of indexes, and the clustering result is shown in table 3.
TABLE 3 clustering results of initial evaluation index of Low carbon benefits
S3, determining weights of 11 kinds of clustered indexes by using an analytic hierarchy process, and according to the table 3, respectively calculating the weights of the indexes in the classes according to the non-unique number of the indexes in the classes 1, 2,6 and 8, so as to select representative indexes; however, only one of the indexes of the 3 rd, 4 th, 5 th, 7 th, 9 th, 10 th and 11 th classes is the unique index, namely the representative index of the class, and the weight is not required to be calculated any more.
The specific conditions of the index weights of the 1 st, 2 nd, 6 th and 8 th classes are calculated as follows:
(1) For class 1 index: u414; u416; u417; u420 weight calculation
① And constructing a judging matrix of the class 1 index.
And comparing the indexes in pairs according to the nine-bit proportion scale table to obtain a judgment matrix.
② The results of the consistency test of the judgment matrix of the class 1 index are shown in table 4.
Table 4 determination matrix consistency test results of class 1
③ The weight calculation results of the class 1 index are shown in table 5.
Table 5 class 1 index weights
④ The index U420 with the largest weight is reserved and is used as a representative index of the class 1 index. (2) for class 2 indicators: u402; u415; u418; u419 weight calculation
① And constructing a judging matrix of the class 2 index.
② The results of the consistency test of the judgment matrix of the class 2 index are shown in table 6.
Table 6 determination matrix consistency test results of class 2
③ The weight calculation results of the class 2 index are shown in table 7.
TABLE 7 class 2 index weight
④ The index U419 with the largest weight is reserved and is used as a representative index of the class 2 index. (3) for class 6 index: u407; u410; u413 weight calculation
① And constructing a judging matrix of the class 6 index.
② The results of the consistency test of the judgment matrix of the class 6 index are shown in table 8.
Table 8 determination matrix consistency test results for class 6 index
③ The weight calculation results of the class 6 index are shown in table 9.
Table 9 class 6 indicator weights
④ The index U413 with the largest weight is reserved as a representative index of the class 6 index.
(4) For class 8 index: u403; u408 weight calculation
① And constructing an 8 th class index judgment matrix.
② The results of the consistency test of the judgment matrix of the class 8 index are shown in table 10.
Table 10 determination matrix consistency test results for class 8 index
③ The weight calculation results of the class 8 index are shown in table 11.
Table 11 class 8 indicator weights
④ The index U408 with the largest weight is reserved and used as a representative index of the class 8 index.
According to the analysis results, in this embodiment, U401, U404, U405, U406, U408, U409, U411, U412, U413, U419, and U420 are finally selected as representative indexes.
S4, calculating the KMO value of the representative index.
S5, obtaining KMO=0.861 > 0.7 of the 11 representative indexes according to a KMO calculation formula, wherein the fact that the whole information of the representative indexes is high in overlapping rate indicates that overlapping indexes exist, and screening needs to be continued.
The number of sample suitability amounts of each representative index was calculated based on KMa i values, and the calculation results are shown in table 12.
TABLE 12 Low carbon benefit representative index KMa i values
As can be seen from table 12, KMa i =0.923 of the grid-side benefit index U408 is the largest, and thus the index U408 is eliminated.
S6, KMO=0.741 > 0.7 of 10 representative indexes remained after the U408 is removed is calculated, which shows that the overlapping correlation of the residual indexes is larger, and according to the table 12, KMa i =0.903 of the electric energy replacement emission reduction benefit U413 is the largest, and the index U413 is removed. And meanwhile, calculating KMO=0.651 < 0.7 of the remaining 9 indexes, which shows that the overlapping correlation of the remaining indexes is small, stopping screening, and obtaining the final low-carbon benefit evaluation indexes as shown in table 13.
TABLE 13 Low carbon benefit final evaluation index
/>
And similarly, energy efficiency indexes, economic indexes, social benefits and enterprise development benefit indexes are screened according to the method.
On the other hand, the embodiment of the invention also discloses an evaluation index screening system of the wind-solar-energy-storage integrated operation system, and referring to fig. 3, the system comprises:
The evaluation system construction module is used for establishing a wind-solar-energy-storage integrated operation multidimensional benefit evaluation system and acquiring initial evaluation indexes;
The clustering module is used for classifying the initial evaluation indexes based on cluster analysis;
The representative index acquisition module is used for calculating the weight of each type of index by adopting an analytic hierarchy process and selecting the index with the largest weight in each type of index as the representative index;
the KMO calculation module is used for calculating KMO coefficients of the representative indexes;
the overlapping index judging module is used for judging whether an overlapping index exists according to the KMO coefficient;
and the output module is used for acquiring a final evaluation index according to the judgment result of the overlapping index.
Further, the clustering module includes:
the standardized processing unit is used for carrying out standardized processing on the initial evaluation index to obtain a standardized index;
A correlation coefficient calculation unit for calculating a correlation coefficient between the evaluation indexes based on the standardized indexes;
The index classification unit is used for combining indexes with correlation coefficients close to a first preset value into one type of indexes, and the indexes with correlation coefficients close to a second preset value are independently used as one type of indexes.
Further, the representative index acquisition module includes:
the judging matrix construction unit is used for constructing a judging matrix of a certain type of indexes;
The consistency checking unit is used for carrying out consistency checking on the judgment matrix and solving the maximum characteristic root and the corresponding characteristic vector of the judgment matrix;
The weight calculation unit is used for calculating index weight according to the maximum characteristic root of the judgment matrix and the corresponding characteristic vector;
The representative index selecting unit is used for selecting the index with the largest weight as the representative index of the index.
Further, the output module includes:
An overlap index processing unit for determining an overlap index according to the sampling suitability quantity of the representative index in the presence of the overlap index, and deleting the overlap index;
And the final evaluation index output unit is used for acquiring a final evaluation index according to the judgment result of the overlapping index.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. The evaluation index screening method of the wind-solar-energy-storage integrated operation system is characterized by comprising the following steps of:
s1, establishing a wind-solar-energy-storage integrated operation multidimensional benefit evaluation system, and acquiring an initial evaluation index;
s2, classifying the initial evaluation index based on cluster analysis;
S3, calculating the weight of each type of index by adopting an analytic hierarchy process, and selecting the index with the largest weight in each type of index as a representative index;
s4, calculating the KMO coefficient of the representative index;
s5, judging whether an overlapping index exists according to the KMO coefficient; if the representative index does not exist, the representative index is used as a final evaluation index; if the sample suitability quantity of the representative index exists, determining the overlapping index, and deleting the overlapping index;
S6, repeating S4-S5 aiming at the representative index after deleting the overlapped index until the overlapped index does not exist, and stopping screening, wherein the rest representative index is a final evaluation index.
2. The method for screening the evaluation index of the wind-solar-energy-storage integrated operation system according to claim 1, wherein the step S2 comprises:
Carrying out standardization treatment on the initial evaluation index to obtain a standardization index;
calculating a correlation coefficient between evaluation indexes based on the standardized indexes;
and merging the indexes of which the correlation coefficients are close to the first preset value into one type of indexes, wherein the indexes of which the correlation coefficients are close to the second preset value are independently used as one type of indexes.
3. The method for screening the evaluation index of the wind-solar-energy-storage integrated operation system according to claim 2, wherein the step S3 comprises:
Constructing a judging matrix of a certain type of indexes;
Consistency test is carried out on the judgment matrix, and the maximum characteristic root and the corresponding characteristic vector of the judgment matrix are solved;
Calculating index weight according to the maximum feature root and the corresponding feature vector of the judgment matrix;
And selecting the index with the largest weight as a representative index of the index.
4. The method for screening the evaluation index of the wind-solar energy-storage integrated operation system according to claim 1, wherein in S5, judging whether the overlapping index exists according to the KMO coefficient comprises the following steps:
Judging whether the KMO coefficient is smaller than a KMO threshold, if so, not existence of the overlapped index, otherwise, existence of the overlapped index.
5. The method for screening the evaluation index of the wind-solar-energy-storage integrated operation system according to claim 1, wherein in S5, determining the overlap index according to the sampling suitability quantity of the representative index comprises:
Calculating the sampling suitability quantity of each representative index respectively;
And taking the representative index with the largest sampling suitability quantity as the overlapping index.
6. An evaluation index screening system of a wind-solar-energy-storage integrated operation system is characterized by comprising:
The evaluation system construction module is used for establishing a wind-solar-energy-storage integrated operation multidimensional benefit evaluation system and acquiring initial evaluation indexes;
The clustering module is used for classifying the initial evaluation indexes based on cluster analysis;
The representative index acquisition module is used for calculating the weight of each type of index by adopting an analytic hierarchy process and selecting the index with the largest weight in each type of index as the representative index;
A KMO calculation module, configured to calculate KMO coefficients of the representative index;
The overlapping index judging module is used for judging whether an overlapping index exists according to the KMO coefficient;
and the output module is used for acquiring the final evaluation index according to the judgment result of the overlapping index.
7. The evaluation index screening system of the wind-solar-energy-storage integrated operation system according to claim 6, wherein the clustering module comprises:
the standardized processing unit is used for carrying out standardized processing on the initial evaluation index to obtain a standardized index;
A correlation coefficient calculation unit for calculating a correlation coefficient between the evaluation indexes based on the standardized indexes;
And the index classification unit is used for combining the indexes of which the correlation coefficients are close to the first preset value into one type of indexes, and the indexes of which the correlation coefficients are close to the second preset value are independently used as one type of indexes.
8. The evaluation index screening system of the wind-solar energy-storage integrated operation system according to claim 7, wherein the representative index acquisition module comprises:
the judging matrix construction unit is used for constructing a judging matrix of a certain type of indexes;
The consistency checking unit is used for carrying out consistency checking on the judgment matrix and solving the maximum characteristic root and the corresponding characteristic vector of the judgment matrix;
the weight calculation unit is used for calculating index weight according to the maximum characteristic root of the judgment matrix and the corresponding characteristic vector;
The representative index selecting unit is used for selecting the index with the largest weight as the representative index of the index.
9. The evaluation index screening system of the wind-solar energy-storage integrated operation system according to claim 6, wherein the output module comprises:
An overlapping index processing unit, configured to determine an overlapping index according to the sampling suitability amount of the representative index when the overlapping index exists, and delete the overlapping index;
And the final evaluation index output unit is used for acquiring the final evaluation index according to the judgment result of the overlapping index.
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