CN113159650A - Optical charging storage system operation benefit evaluation method based on improved matter element extension model - Google Patents

Optical charging storage system operation benefit evaluation method based on improved matter element extension model Download PDF

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CN113159650A
CN113159650A CN202110558591.4A CN202110558591A CN113159650A CN 113159650 A CN113159650 A CN 113159650A CN 202110558591 A CN202110558591 A CN 202110558591A CN 113159650 A CN113159650 A CN 113159650A
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朱国荣
董丹煌
王洪良
文凡
胡嘉骅
杨侃
叶玲节
孙秋洁
朱瑶琪
杨云露
张一泓
冯也
彭莎
陆易凡
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North China Electric Power University
Economic and Technological Research Institute of State Grid Zhejiang Electric Power Co Ltd
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Economic and Technological Research Institute of State Grid Zhejiang Electric Power Co Ltd
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Abstract

本发明公开了属于电力系统技术领域的一种基于改进物元可拓模型的光充储系统运营效益评价方法。该方法包括以下步骤：步骤1：初步构建运营效益评价指标体系并对上述指标的指标值进行样本数据采集，然后对样本的准则层判断矩阵进行归一化处理；步骤2：采用层次分析法与熵权法，综合主客观因素确定光充储系统运营效益综合评价指标的权重；步骤3：以经典物元可拓模型为基础，通过引入最大接近经典域中值确定关联度的计算方法形成改进的物元可拓模型，从而对光充储系统运营效益进行综合评价。本发明可以进一步提高光充储系统运营效益分析的标准化和有效性，更加全面地反映当前光充储系统的运营情况，且更加可靠地支持企业的未来经营决策。

Figure 202110558591

The invention discloses an operation benefit evaluation method of an optical charging and storage system based on an improved matter-element extension model, belonging to the technical field of electric power systems. The method includes the following steps: Step 1: Preliminarily construct an operation benefit evaluation index system and collect sample data for the index values of the above-mentioned indicators, and then normalize the criterion-level judgment matrix of the sample; Step 2: adopt the AHP and The entropy weight method combines subjective and objective factors to determine the weight of the comprehensive evaluation index of the operational benefit of the optical storage system; Step 3: Based on the classical matter-element extension model, an improvement is formed by introducing the calculation method that is most close to the median value of the classical domain to determine the degree of correlation The matter-element extension model is used to comprehensively evaluate the operational benefits of the optical storage system. The invention can further improve the standardization and effectiveness of the operation benefit analysis of the optical charging and storage system, more comprehensively reflect the current operation of the optical charging and storage system, and more reliably support the future business decision of the enterprise.

Figure 202110558591

Description

Optical charging storage system operation benefit evaluation method based on improved matter element extension model
Technical Field
The invention relates to the technical field of power systems, in particular to an operation benefit evaluation method of a light charging storage system based on an improved matter element extension model.
Background
The energy storage technology is the key for improving the utilization rate of renewable energy, and is continuously developed and innovated at present when the renewable energy is developed at a high speed. Through development for many years, the photovoltaic power generation industry has become a strategic emerging industry in China. However, with the wide construction and grid connection of the photovoltaic power station, problems such as light abandonment and electricity limitation, photovoltaic power consumption, difficulty in predicting photovoltaic output and the like are increasingly prominent, which causes great influence on the safe and stable operation of the power system, and leads to further popularization and grid connection of the photovoltaic power station to be increasingly difficult.
The energy storage equipment can well deal with the characteristics of strong fluctuation of photovoltaic power generation in time and nonuniform space, and the establishment and application of an energy storage system can ensure that photovoltaic electric quantity is continuously and stably connected into a power grid in a large scale. In recent years, the energy storage technology is rapidly developed, and with the reduction of the cost of the energy storage battery, the increase of the life cycle and the improvement of the use efficiency, the energy storage is developed to a large capacity and a large scale from small-capacity and small-scale research and demonstration. The energy storage system developed in a large scale is combined with the photovoltaic power generation system, so that the formed light storage and charging system can absorb off-peak electricity by using the battery energy storage system, supports a quick charging load in a peak period, is supplemented by the photovoltaic power generation system, effectively reduces the power grid load of a charging station in the peak period, improves the operation efficiency of the system and provides an auxiliary service function for a power grid.
Whether the optical charging and storing system can be put into use or not, firstly, the operation benefit must be considered. Many researchers start to research the economy of the optical storage system from the perspective of energy storage optimization configuration, but the research of comprehensive evaluation and analysis of the operation benefits of the optical storage and energy storage combined system is less, and the research of some comprehensive evaluation of the benefits also has the problem that an index system is less in construction or a proper algorithm model is not adopted for development and evaluation.
The method comprises the steps of analyzing the economical efficiency of the light charging and storing combined system, developing evaluation on the operation benefit of the light charging and storing system, establishing a relatively complete and comprehensive operation benefit index evaluation system from the aspects of profitability, debt paying capacity, operation capacity and income level, determining the weight of the comprehensive operation benefit evaluation index of the light charging and storing system by adopting a combined Analytic Hierarchy Process (AHP) and an entropy weight method, and introducing a calculation method for determining the relevance degree by maximally sticking to the median in a classical domain on the basis of a classical matter-element model to realize the comprehensive evaluation on the operation benefit of the light charging and storing system.
Disclosure of Invention
The invention aims to provide an optical charging and storing system operation benefit evaluation method based on an improved matter element extension model, which is characterized by comprising the following steps of:
step 1: data acquisition and pretreatment; according to the technical characteristics and functions of the optical charging and storing system, selecting indexes from the four aspects of profitability, debt paying capacity, operation capacity and income level, preliminarily constructing an operation benefit evaluation index system, collecting sample data of the index values of the indexes, and then carrying out normalization processing on a criterion layer judgment matrix of the sample;
step 2: determining the combined weight of the evaluation indexes; determining the weight of the comprehensive evaluation index of the operational benefit of the optical charge storage system by integrating subjective and objective factors by adopting an analytic hierarchy process and an entropy weight method;
and step 3: performing operation benefit evaluation on the optical charging and storing system based on the matter element extension model; based on the classical matter element extension model, an improved matter element extension model is formed by introducing a calculation method of determining the degree of association by being maximally close to the median of the classical domain, so that the operation benefits of the optical storage system are comprehensively evaluated.
The method for performing normalization processing on the criterion layer judgment matrix of the sample in the step1 specifically comprises the following steps:
assuming that n evaluation indexes and m evaluation objects are provided, an index matrix X ═ X is first constructedij)m×nThen, carrying out non-dimensionalization on the index matrix:
Figure BDA0003078063500000021
wherein, x'ijA value representing the j-th evaluation index of the i-th evaluation object after the index matrix standardization; x is the number ofijA numerical value indicating a j-th evaluation index of an i-th evaluation object; min (x)j) Represents the minimum value in the jth evaluation index; max (x)j) Represents the maximum value of the j-th evaluation index.
In the step2, the specific steps of subjectively weighting by adopting an analytic hierarchy process are as follows:
step C1: establishing a judgment matrix; quantifying the judgment by adopting a nine-level scale method, and constructing a judgment matrix U-U (U-U) according to the importance of the indexes of the same level relative to the indexes of the upper layerij)n×n；
Step C2: sorting the hierarchical lists, and carrying out consistency check; judging the matrix U ═ U by solvingij)n×nThe feature root problem of (a) is to obtain a feature vector W and normalize the feature vector W to obtain a standard matrix a ═ aij)n×nObtaining the relative importance of the hierarchical element to the corresponding upper hierarchical element; calculating a consistency index
Figure BDA0003078063500000022
Wherein λmaxFor the maximum eigenvalue, the consistency of the judgment matrix is checked, and when the check coefficient is satisfied
Figure BDA0003078063500000031
Then, wherein RI is an average random consistency index, and the judgment matrix is considered to have satisfactory consistency;
step C3: overall hierarchical sorting; sequentially calculating from top to bottom layer by layer along the hierarchical structure, and calculating the synthetic weight W of the bottommost layer relative to the highest layer of the target layer1＝[ν1,ν2,…,νm]T。
In the step2, the entropy weight method is adopted to carry out objective weighting, and the specific steps are as follows:
step S1: acquiring an information entropy; information entropy EjThe calculation formula is as follows:
Figure BDA0003078063500000032
Figure BDA0003078063500000033
in the formula, PijThe j index accounts for the specific gravity of the j index in the ith evaluation object;
step S2: calculating the entropy values of the profitability index, the repayment ability index and the operation ability index and the objective weight of the evaluation factors of each target layer; the information entropy normalization processing is carried out to obtain index weight, and the calculation formula is as follows:
Figure BDA0003078063500000034
in the formula, vjRepresents the weight of the j-th index.
In the step2, the weight for determining the comprehensive evaluation index of the operation benefit of the optical charging and storage system by synthesizing the subjective and objective factors is specifically as follows:
ri＝αWi+βVi (5)
in the formula, riWeights to weight the combinations; wiSubjective weights determined for the analytic hierarchy process; viAn objective weight determined for the entropy weight method; α and β represent the importance of the objective weight, and α is 0.5 and β is 0.5.
In the step3, the specific steps of comprehensively evaluating the operation benefits of the optical charging and storage system by adopting the improved matter element extension model are as follows:
step D1: determining classical domains
Figure BDA0003078063500000041
In the formula: u shapejJ divided evaluation levels; c1,C2,…,CnTo evaluate the index system; xjnTo evaluate the grade UjEvaluation index CnA defined magnitude range, Xjn＝(ajn,bjn)，ajnAnd bjnMinimum and maximum values of the magnitude range, respectively;
step D2: determining section domains
Figure BDA0003078063500000042
In the formula: u shapepThe whole evaluation grade is obtained; interval Xpn＝(apn,bpn) Is UpWith respect to CnThe specified magnitude range, i.e., section domain;
step D3: determining a degree of association
Figure BDA0003078063500000043
In the formula, Kj(xi) The correlation function value of the ith index for the jth grade; ρ (x)i,xin) The distance between the element value to be evaluated of the ith index and the classical domain; | ρinL is the distance of the ith index with respect to the jth level classical domain;
when x isi∈X1And ask for K1(xn) The method comprises the following steps:
Figure BDA0003078063500000044
when x isi∈XmAnd ask for Km(xn) The method comprises the following steps:
Figure BDA0003078063500000045
in other cases:
Figure BDA0003078063500000046
step D4: determining a comprehensive degree of association
Comprehensive relevance K of object to be evaluated to each evaluation gradej(pij) The calculation formula is as follows:
Kj(pij)＝∑σiKj(xi) (12)
in the formula, pijIs an object to be evaluated; sigmaiIs the weight of the ith evaluation index.
The invention has the beneficial effects that:
by providing the comprehensive evaluation method for the operation benefit of the optical charging and storing system for improving the matter element extension model, the standardization and the effectiveness of the operation benefit analysis of the optical charging and storing system can be further improved, the operation condition of the current optical charging and storing system can be more comprehensively reflected, and the future operation decision of an enterprise can be more reliably supported.
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Fig. 1 is a general flowchart of an operation benefit evaluation method of an optical charging and storage system based on an improved matter element extension model.
Detailed Description
The invention provides an improved matter element extension model-based operation benefit evaluation method for an optical charging and storing system, which is further described with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a general flowchart of an operation benefit evaluation method of an optical charging and storage system based on an improved matter element extension model. The method provided by the invention is applied to comprehensively evaluate the light charging, storage and transportation benefits in Zhejiang province, an index system for evaluating the light charging, storage and transportation benefits is established by collecting relevant data, and the comprehensive evaluation on the economic benefits of the light charging, storage and transportation system is carried out based on an improved matter element extension model.
1. Construction of comprehensive evaluation index system for operation benefit of optical charging and storage system
The method is used for objectively, comprehensively and scientifically reflecting the operation benefits of the optical charging and storing system, providing a reliable decision basis for a decision maker, selecting relevant indexes from the four aspects of profitability, repayment ability, operation ability, income level and the like, and initially constructing an economic activity evaluation index system. Meanwhile, a Delphi method is adopted to invite related industry experts, the opinions of the industry experts on the primary selection indexes are requested anonymously, the opinions are summarized and fed back, and finally, an optical charge storage system operation benefit comprehensive evaluation index system shown in the table 1 is determined.
TABLE 1
Figure BDA0003078063500000061
(1) Profitability
The profitability guarantees the long-term healthy development of enterprises, and 5 corresponding three-level indexes are further constructed, namely total investment earning rate, financial net present value, investment recovery period, capital fund net earning rate and internal earning rate.
(2) Ability to pay off debt
Whether the enterprise has the cash payment capability and the debt payment capability is the key for the healthy survival and development of the enterprise, and 3 corresponding three-level indexes, namely a borrowing and repayment period, an asset liability rate and an interest reserve rate, should be further constructed.
(3) Operational capacity
The operation capacity represents the consumption level and the stability level of photovoltaic power generation, 4 corresponding three-level indexes are further constructed, namely the reduction of the photovoltaic light rejection rate, the photovoltaic grid connection and consumption, the power supply reliability of a light storage system and the reduction of the power deviation punishment cost.
(4) Profit level
The income level is the fundamental power of economic activities carried out by power grid enterprises, and 6 corresponding three-level indexes are further constructed, namely low storage and high discharge income, government subsidy income, system photovoltaic electric quantity income, retired power battery recycling benefit, capacity and electricity charge income reduction and holiday photovoltaic surplus internet access income.
Data acquisition:
each index data of a certain optical charging and storage system operation benefit evaluation index system is shown in table 2:
TABLE 2
Index (I) Index data Unit of
Total throwRate of return 5.08 ％
Net present financial value 13.25 Wan Yuan
Period of investment recovery 6.56 Wan Yuan
Net profit margin of capital fund 10.92 ％
Internal rate of return 6.90 ％
Loan repayment period 14 Year of year
Rate of assets and liabilities 79.86 ％
Rate of interest reserve 1.50 ％
Reduction of photovoltaic rejection 1.90 ％
Photovoltaic grid connection and absorption 719 Thousands of kilowatts
Power supply reliability of optical storage system 9 Wan Yuan
Reducing power offset penalty cost 0.5 Element/kw
Low reserve high gain 13.4 Wan Yuan
Government subsidy revenue 50 Universal seat
System photovoltaic power yield 18.1 Wan Yuan
Recycling benefit of retired power battery 48 Ten thousand yuan/festival
Reducing capacity charges for electricity revenue 75.6 Wan Yuan
Photovoltaic surplus internet access income in holidays 5.3 Wan Yuan
2. Operation benefit evaluation index empowerment
(1) Standardization of evaluation index
Because different evaluation indexes have differences in measurement units and economic meanings and have different evaluation effects on the total target, the index values are subjected to standardized treatment and then comprehensively evaluated, so that the adverse effect of the index differences is weakened, and the objectivity of the evaluation process and the results is enhanced. The overall index was treated as follows:
STEP 1: and (6) standardizing data. Assuming that n evaluation indexes and m evaluation objects are provided, an index matrix X ═ X is first constructedij)m×nAnd then, carrying out non-dimensionalization processing on the index matrix. The treatment method is as follows:
Figure BDA0003078063500000081
(2) determining evaluation index combination weights
And determining the operation benefit of the light charging and storing system by integrating subjective and objective factors through an Analytic Hierarchy Process (AHP) and an entropy weight method.
The method adopts an analytic hierarchy process to subjectively weight the designed three-layer index system, and comprises the following specific processes:
step 1: comparing two by two to establish a judgment matrix
Consulting expert opinions, quantifying judgment by adopting a nine-level scale method, constructing a judgment matrix, and constructing the judgment matrix U (U) by adopting the nine-level scale method according to the importance of the indexes of the same level relative to the indexes of the upper layerij)n×n。
Step 2: hierarchical single ordering and consistency checking
Judging the matrix U ═ U by solvingij)n×nAnd (4) obtaining a feature vector W by the feature root problem, and normalizing to obtain a ranking weight of the hierarchical element relative to the corresponding upper hierarchical element.
Calculating a consistency index
Figure BDA0003078063500000082
Performing consistency check of the judgment matrix when the judgment matrix is satisfied
Figure BDA0003078063500000083
The decision matrix is considered to have satisfactory consistency.
Step 3: total ordering of layers
Sequentially calculating from top to bottom layer by layer along the hierarchical structure, and calculating the synthetic weight W of the bottommost layer relative to the target layer (the highest layer)1＝[ν1,ν2,…,νm]T
Secondly, an entropy weight method is adopted, known data are utilized to objectively weight the index system, and the method comprises the following specific steps:
STEP 1: and acquiring the information entropy. Information entropy EjThe calculation formula is as follows:
Figure BDA0003078063500000084
Figure BDA0003078063500000085
STEP 2: and calculating the entropy values of the profit storage capacity index, the repayment capacity index and the operation capacity index and the objective weight of the evaluation factors of each target layer. The information entropy normalization processing is carried out to obtain index weight, and the calculation formula is as follows:
Figure BDA0003078063500000091
combining weighting, and combining a subjective weighting method and an objective weighting method according to different preference coefficients to determine the index weight. The calculation formula is as follows:
ri＝αWi+βVi (5)
in the formula, WiSubjective weights determined for the analytic hierarchy process; viThe index weight determined for the entropy weight method (here, α ═ 0.5, β ═ 0.5) yields W ═ ω ═ ω1,ω2,…,ωn]TNamely, the evaluation index combined weight vector is obtained.
Through an analytic hierarchy process and an entropy weight process, the main weight and the objective weight of the economic activity comprehensive evaluation index are respectively determined, the combined weight of the operation benefit comprehensive evaluation index of the optical storage system can be obtained, and the result of the combined weight is shown in table 3.
TABLE 3 evaluation index combination weights
Figure BDA0003078063500000092
3. Improved matter element extension model
Based on the classical matter element model, when the association degree of the matter elements is calculated through the association function, the higher the association degree of the indexes is, the more obvious the membership relationship is when the matter elements are closer to the highest or lowest grade, so that the operation benefit of the light charging and storage system is comprehensively evaluated, and the change rule among the matter elements is more effectively analyzed.
The improved matter element combination evaluation steps are as follows:
step 1: determining classical domains
Figure BDA0003078063500000101
In the formula: u shapejJ divided evaluation levels; c1,C2,…,CnTo evaluate the index system; xjiTo evaluate the grade UjEvaluation index CnA defined magnitude range, Xjn＝(ajn,bjn)。
Step 2: determining section domains
Figure BDA0003078063500000102
In the formula: u shapepThe whole evaluation grade is obtained; interval Xpn＝(apn,bpn) Is UpWith respect to CnThe specified magnitude range, the section domain.
Step 3: determining a degree of association
The correlation function can embody the operation benefit level of the index, embody the correlation degree between the evaluated unit and the evaluation grade thereof, and describe the benefit degree of each index through the grade level.
Figure BDA0003078063500000103
When x isi∈X1And ask for K1(xn) The method comprises the following steps:
Figure BDA0003078063500000104
when x isi∈XmAnd ask for Km(xn) The method comprises the following steps:
Figure BDA0003078063500000105
in other cases:
Figure BDA0003078063500000106
step 4: determining a comprehensive degree of association
Comprehensive relevance K of object to be evaluated to each evaluation gradej(pij) The calculation formula is as follows:
Kj(pij)＝∑σiKj(xi) (12)
in the formula, σiIs the weight of the ith evaluation index.
The profitability index, the repayment ability index, the operation ability and the income level index of the operation benefit of the optical charging and storage system are divided into five grades of 'poor', 'normal', 'good' and 'good', an improved matter element extension model is established, comprehensive evaluation is carried out on the comprehensive evaluation index and evaluation grade data of economic activities, and finally the maximum comprehensive relevance degree and evaluation grade result of the comprehensive evaluation of the optical charging and storage system are calculated and shown in table 4.
TABLE 4 maximum comprehensive degree of association and evaluation grade of evaluation indexes of each target layer
Operational benefits Maximum integrated degree of association Comprehensive evaluation grade
Profitability 0.1989 In general
Ability to pay off debt 0.7898 Is preferably used
Operational capacity 0.0724 Good taste
Profit level 0.1197 Good taste
From the above, the comprehensive benefits of a certain optical charging and storage system are rated according to the maximum comprehensive relevance, so that the profit capacity of the optical charging and storage system can be evaluated as general, the repayment capacity can be evaluated as good, and the operation capacity and the income level can be evaluated as good.
In conclusion, the improved object element extension model provided by the invention can realize scientific and effective evaluation on the comprehensive benefits of the optical charge storage system. Firstly, respectively calculating subjective and objective weights of 18 economic activity evaluation indexes by an analytic hierarchy process and an entropy weight process, and performing weight combination; and secondly, comprehensively evaluating the benefits of the optical storage system by adopting an improved matter element extension model, calculating the corresponding maximum comprehensive relevance based on the comprehensive evaluation, and dividing five grades of 'poor', 'common', 'good' and 'good' according to the comprehensive benefit level of the optical storage system so as to further reflect the trend of the economic activity rating. According to example verification, the result obtained by the comprehensive evaluation of the model is consistent with the actual situation.
The present invention is not limited to the above embodiments, and any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention are also within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (6)

1.一种基于改进物元可拓模型的光充储系统运营效益评价方法，其特征在于，包括以下步骤：1. a method for evaluating the operational benefit of an optical charging and storage system based on an improved matter-element extension model, is characterized in that, comprises the following steps: 步骤1：数据采集与预处理；依据光充储系统的技术特征和职能，从盈利能力、偿债能力、营运能力以及收益水平四个方面选取指标，初步构建运营效益评价指标体系并对上述指标的指标值进行样本数据采集，然后对样本的准则层判断矩阵进行归一化处理；Step 1: Data collection and preprocessing; according to the technical characteristics and functions of the optical storage system, select indicators from the four aspects of profitability, solvency, operating capacity and income level, and initially construct an operational benefit evaluation index system and analyze the above indicators. The index value of the sample is collected, and then the criterion layer judgment matrix of the sample is normalized; 步骤2：确定评价指标组合权重；采用层次分析法与熵权法，综合主客观因素确定光充储系统运营效益综合评价指标的权重；Step 2: Determine the weight of the combination of evaluation indicators; use the AHP and entropy weight method to combine subjective and objective factors to determine the weight of the comprehensive evaluation index of the operational benefit of the optical storage system; 步骤3：基于物元可拓模型对光充储系统进行运营效益评价；以经典物元可拓模型为基础，通过引入最大接近经典域中值确定关联度的计算方法形成改进的物元可拓模型，从而对光充储系统运营效益进行综合评价。Step 3: Based on the matter-element extension model to evaluate the operational benefit of the optical storage system; based on the classical matter-element extension model, an improved matter-element extension is formed by introducing a calculation method that is most close to the median value of the classical domain to determine the correlation degree The model can be used to comprehensively evaluate the operational benefits of the optical charging and storage system. 2.根据权利要求1所述的基于改进物元可拓模型的光充储系统运营效益评价方法，其特征在于，所述步骤1中对样本的准则层判断矩阵进行归一化处理的方法具体如下：2. The method for evaluating the operational benefit of an optical charging and storage system based on an improved matter-element extension model according to claim 1, wherein the method for normalizing the criterion layer judgment matrix of the sample in the step 1 is concrete. as follows: 假设有n个评价指标，m个评价对象，首先构建指标矩阵X＝(xij)m×n，然后对指标矩阵进行无量纲化处理：Assuming there are n evaluation indicators and m evaluation objects, first construct an indicator matrix X=(x ij ) m×n , and then perform dimensionless processing on the indicator matrix:
Figure FDA0003078063490000011
Figure FDA0003078063490000011
 其中，x′ij表示指标矩阵标准化处理后第i个评价对象的第j个评价指标的数值；xij表示第i个评价对象的第j个评价指标的数值；min(xj)表示第j个评价指标中的最小值；max(xj)表示第j个评价指标中的最大值。Among them, x′ ij represents the value of the jth evaluation index of the ith evaluation object after the standardization of the index matrix; x ij represents the value of the jth evaluation index of the ith evaluation object; min(x j ) represents the jth evaluation index The minimum value among the evaluation indexes; max(x j ) represents the maximum value among the jth evaluation indexes. 3.根据权利要求1所述的基于改进物元可拓模型的光充储系统运营效益评价方法，其特征在于，所述步骤2中，采用层次分析法进行主观赋权的具体步骤如下：3. The method for evaluating the operational benefit of an optical storage system based on an improved matter-element extension model according to claim 1, characterized in that, in the step 2, the specific steps of adopting AHP to carry out subjective weighting are as follows: 步骤C1：建立判断矩阵；采用九级标度法将判断定量化，根据同层级指标相对上层指标的重要性，构建判断矩阵U＝(uij)n×n；Step C1: establish a judgment matrix; adopt the nine-level scaling method to quantify the judgment, and construct a judgment matrix U=(u ij ) n×n according to the importance of the indexes of the same level relative to the indexes of the upper level; 步骤C2：层次单排序，并进行一致性检验；通过求解判断矩阵U＝(uij)n×n的特征根问题，得到特征向量W，并进行归一化得到标准矩阵A＝(aij)n×n，得到该层次元素对于相应上层次元素相对重要性的排序权值；计算一致性指标
Figure FDA0003078063490000021
其中λmax为最大特征值，进行判断矩阵的一致性检验，当满足检验系数
Figure FDA0003078063490000022
时，其中RI为平均随机一致性指标，认为判断矩阵具有满意的一致性；Step C2: Single-level sorting and consistency check; by solving the characteristic root problem of the judgment matrix U=(u ij ) n×n , the eigenvector W is obtained, and normalized to obtain the standard matrix A=(a ij ) n×n , get the ranking weight of the relative importance of the element of this level to the element of the corresponding upper level; calculate the consistency index
Figure FDA0003078063490000021
Among them, λ max is the largest eigenvalue, and the consistency test of the judgment matrix is carried out. When the test coefficient is satisfied
Figure FDA0003078063490000022
, where RI is the average random consistency index, and the judgment matrix is considered to have satisfactory consistency; 步骤C3：层次总排序；依次沿递阶层次结构由上而下逐层计算，计算出最底层相对于目标层最高层的合成权重W1＝[ν1,ν2,…,νm]T。Step C3: total ordering of the hierarchy; calculate layer by layer along the hierarchical structure from top to bottom, and calculate the composite weight W 1 =[ν 1 ,ν 2 ,...,ν m ] T of the lowest layer relative to the highest layer of the target layer . 4.根据权利要求1所述的基于改进物元可拓模型的光充储系统运营效益评价方法，其特征在于，所述步骤2中，采用熵权法进行客观赋权的具体步骤如下：4. The method for evaluating the operational benefit of an optical charging and storage system based on an improved matter-element extension model according to claim 1, wherein in the step 2, the specific steps of using the entropy weight method to carry out objective weighting are as follows: 步骤S1：获取信息熵；信息熵Ej计算公式如下：Step S1: obtain information entropy; the calculation formula of information entropy E j is as follows:
Figure FDA0003078063490000023
Figure FDA0003078063490000023
Figure FDA0003078063490000024
Figure FDA0003078063490000024
 式中，Pij表示第j项指标在第i个评价对象中占该指标的比重；In the formula, P ij represents the proportion of the j-th index in the i-th evaluation object; 步骤S2：计算盈利能力指标、偿债能力指标、营运能力指标的熵值及各目标层评价因素的客观权重；对信息熵归一化处理获得指标权重，其计算公式如下：Step S2: Calculate the entropy value of the profitability index, the solvency index, the operating ability index and the objective weight of the evaluation factors of each target layer; normalize the information entropy to obtain the index weight, and the calculation formula is as follows:
Figure FDA0003078063490000025
Figure FDA0003078063490000025
 式中，vj表示第j项指标的权重。In the formula, v j represents the weight of the j-th index. 5.根据权利要求1所述的基于改进物元可拓模型的光充储系统运营效益评价方法，其特征在于，所述步骤2中，综合主客观因素确定光充储系统运营效益综合评价指标的权重具体为：5. The method for evaluating the operational benefits of an optical storage system based on an improved matter-element extension model according to claim 1, wherein in the step 2, a comprehensive evaluation index of the operational benefit of the optical storage system is determined by combining subjective and objective factors The weights are specifically: ri＝αWi+βVi (5)r i =αW i +βV i (5) 式中，ri为组合赋权的权重；Wi为层次分析法确定的主观权重；Vi为熵权法确定的客观权重；α和β分别表示主、客观权重的重要度，取α＝0.5,β＝0.5。In the formula, ri is the weight of the combined weighting; Wi is the subjective weight determined by the AHP; Vi is the objective weight determined by the entropy weight method; α and β represent the importance of the subjective and objective weights, respectively, take α= 0.5, β=0.5. 6.根据权利要求1所述的基于改进物元可拓模型的光充储系统运营效益评价方法，其特征在于，所述步骤3中，采用改进的物元可拓模型对光充储系统运营效益进行综合评价的具体步骤如下：6. The method for evaluating the operation benefit of an optical charging and storage system based on an improved matter-element extension model according to claim 1, wherein in the step 3, the improved matter-element extension model is used to operate the optical charging and storage system. The specific steps for comprehensive evaluation of benefits are as follows: 步骤D1：确定经典域Step D1: Determine the Classical Domain
Figure FDA0003078063490000031
Figure FDA0003078063490000031
 式中：Uj为所划分的j个评价等级；C1,C2,…,Cn为评价指标体系；Xjn为评价等级Uj关于评价指标Cn所规定的量值范围，Xjn＝(ajn,bjn)，ajn和bjn分别为量值范围的最小值和最大值；In the formula: U j is the divided j evaluation grades; C 1 , C 2 , ..., C n is the evaluation index system; X jn is the value range specified by the evaluation grade U j about the evaluation index C n , X jn =(a jn , b jn ), a jn and b jn are the minimum and maximum values of the magnitude range, respectively; 步骤D2：确定节域Step D2: Determine the Section Domain
Figure FDA0003078063490000032
Figure FDA0003078063490000032
 式中：Up为整个评价等级；区间Xpn＝(apn,bpn)为Up关于Cn所规定的量值范围，即节域；In the formula: U p is the entire evaluation level; the interval X pn = (a pn , b pn ) is the magnitude range specified by U p about C n , that is, the section field; 步骤D3：确定关联度Step D3: Determine the degree of association
Figure FDA0003078063490000033
Figure FDA0003078063490000033
 式中，Kj(xi)为第i个指标对于第j个等级的关联函数值；ρ(xi,xin)为第i个指标的待评物元值与经典域的距；|ρin|为第i个指标关于第j个等级经典域的距；In the formula, K j ( xi ) is the correlation function value of the ith index for the j th level; ρ(x i , x in ) is the distance between the matter-element value of the ith index to be evaluated and the classical domain; | ρ in | is the distance between the i-th index and the j-th level classical domain; 当xi∈X1且求K1(xn)时：When x i ∈X 1 and find K 1 (x n ):
Figure FDA0003078063490000041
Figure FDA0003078063490000041
 当xi∈Xm且求Km(xn)时：When x i ∈X m and find K m (x n ):
Figure FDA0003078063490000042
Figure FDA0003078063490000042
 其他情况下：In other cases:
Figure FDA0003078063490000043
Figure FDA0003078063490000043
 步骤D4：确定综合关联度Step D4: Determine Comprehensive Relevance 待评价对象对于各评价等级的综合关联度Kj(pij)计算公式为：The calculation formula of the comprehensive correlation degree K j (pi j ) of the object to be evaluated for each evaluation level is: Kj(pij)＝∑σiKj(xi) (12)K j (p ij )=∑σ i K j (x i ) (12) 式中，pij为待评价对象；σi为第i个评价指标的权重。In the formula, p ij is the object to be evaluated; σ i is the weight of the ith evaluation index.
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