CN111814099A - Electrochemical energy storage system evaluation method for guiding bid-inviting purchase - Google Patents
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Abstract
An electrochemical energy storage system evaluation method for guiding bid-attracting purchase belongs to the technical field of energy storage performance evaluation. The method comprises the following steps: step S01, obtaining evaluation index sets of a plurality of target systems; step S02, acquiring a data matrix of the evaluation index corresponding to the target system based on the evaluation index set; step S03, obtaining an evaluation case of the known electrochemical energy storage system, wherein the evaluation case comprises an evaluation result of the electrochemical energy storage system; step S04, determining a subjective weight value set corresponding to the evaluation index set; step S05, determining an objective weight value set corresponding to the evaluation index set; step S06, calculating a comprehensive weight value of the evaluation index according to the subjective weight value in the subjective weight value set and the objective weight value in the objective weight value set; and step S07, calculating the score of the target system according to the comprehensive weight value of the evaluation index. The electrochemical energy storage system is comprehensively evaluated by combining subjective and objective factors, and the evaluation is accurate and efficient.
Description
Technical Field
The invention belongs to the technical field of energy storage performance evaluation, and particularly relates to an electrochemical energy storage system evaluation method for guiding bidding purchase.
Background
When the electrochemical energy storage systems are bid, performance differences caused by different technical emphasis among different energy storage systems or different brands of the same energy storage systems are huge, and evaluation indexes needing to be referred to during bid evaluation are large in quantity and are often selected through experience and subjective judgment. However, for the emerging energy storage technology, subjective and empirical judgment is conservative, and the gold period for the application of the emerging technology is missed.
The invention patent application CN201610907609.6 discloses a method and a system for evaluating the energy storage applicability of a power system, and particularly discloses that the method comprises the steps of determining the application occasion of an energy storage device; the application occasions comprise a power generation side, a power transmission side, a power distribution side and a user side of the power system; acquiring basic evaluation data of the energy storage device; the basic evaluation data is the actual numerical value of each index factor in each index factor set; the index factor set is a set of index factors corresponding to a preset evaluation criterion in a pre-constructed index evaluation system; evaluating each evaluation criterion independently to obtain independent evaluation results of the energy storage device under each evaluation criterion; and comprehensively evaluating all the evaluation criteria to obtain the comprehensive evaluation result of the energy storage device under all the evaluation criteria.
According to the evaluation method disclosed by the patent, the energy storage system is divided into five grades of 'good', 'common', 'poor' and 'poor', the degree of division is low, the energy storage systems with similar performance can be divided into the same grade, and the guidance for bidding and tendering work is insufficient.
Disclosure of Invention
The invention provides an electrochemical energy storage system evaluation method for guiding bidding purchase aiming at the problems in the prior art, which can comprehensively determine the index weight of the electrochemical energy storage system by combining subjective and objective factors and then determine the comprehensive score of the electrochemical energy storage system. The grading can evaluate the relative merits of various energy storage technologies in a specific scene, has quite high discrimination on the similar energy storage technologies of different companies, and can effectively guide the electrochemical energy storage system to bid.
The invention is realized by the following technical scheme:
an electrochemical energy storage system evaluation method for guiding tender procurement comprises the following steps:
step S01, obtaining evaluation index sets of a plurality of target systems;
step S02, acquiring a data matrix of the evaluation index corresponding to the target system based on the evaluation index set;
step S03, obtaining an evaluation case of the known electrochemical energy storage system, wherein the evaluation case comprises an evaluation result of the electrochemical energy storage system;
step S04, determining a subjective weight value set corresponding to the evaluation index set;
step S05, determining an objective weight value set corresponding to the evaluation index set;
step S06, calculating a comprehensive weight value of the evaluation index according to the subjective weight value in the subjective weight value set and the objective weight value in the objective weight value set;
and step S07, calculating the score of the target system according to the comprehensive weight value of the evaluation index.
The method comprises the steps of establishing a subjective evaluation system by utilizing the evaluation cases of the known electrochemical energy storage system, objectively correcting the evaluation system by utilizing the rough set principle to analyze parameter relationships, determining the index weight of the electrochemical energy storage system by integrating subjective and objective factors, calculating the comprehensive scores of different electrochemical energy storage systems according to the weights, evaluating the different energy storage systems by intuitive scores, and finally achieving the purpose of guiding the electrochemical energy storage system to bid.
Preferably, the step S04 includes: according to the application requirements of the energy storage system and the evaluation results in the evaluation cases, different evaluation indexes are ranked from high to low according to the importance degree, and a subjective weight value set with the sum of 1 is set according to the ranking.
Preferably, the step S05 includes:
step S51, discretizing the data matrix;
step S52, calculating the indistinguishable relation of the evaluation index set by using the rough set principle from the data matrix after the discretization processing, and calculating the importance set of the evaluation index set;
and step S53, determining an objective weight value set corresponding to the evaluation index set according to the importance set.
Preferably, the discretization processing method of step S51 is one of the following two methods: the condition discretization method comprises the following steps: comparing the evaluation index score reference table, converting the data of the data matrix into scores, and obtaining a condition discretization data matrix;
two-stage discretization method: scoring data of the data matrix, wherein the maximum value of the parameter of the ith index is full score, the minimum value of the parameter of the ith index is zero score, and the rest parameters of the ith index are distributed between the zero score and the full score according to the proportion; and taking the average value of the data of each evaluation index in the scored data matrix as a boundary, classifying the data of the evaluation index into two grades, and obtaining a two-stage discretization matrix.
As a preference, the first and second liquid crystal compositions are,
when the conditional discretization method is adopted in step S51, the important point in step S52 isImportance sig ({ c) of each evaluation index of degree seti}) is calculated according to the following formula:
wherein, U is the set of all data under the evaluation index, PkThe evaluation index is a set of k grades under the evaluation index, and m is the total number of the grades of the evaluation index;
when the two-stage discretization method is adopted in step S51, the importance sig ({ c) of each evaluation index of the importance set in step S52i}) is equal to the number U of the energy storage systems which can be distinguished after the two-stage discretization matrix deletes the data of the evaluation indexi。
Preferably, the step S53 includes calculating an objective weight value for each evaluation index according to the following formula:
preferably, the step S06 includes: the determination of the comprehensive weight value of the evaluation index is obtained by the following formula:
wherein ω isiIs the integral weight value, omega, of the ith indexsiAnd ωoiThe subjective weight value and the objective weight value of the ith index are respectively, and f is an experience factor.
Preferably, in step S08, if the scoring result in step S07 is determined to be consistent with the evaluation result in the evaluation case, the subjective weight values in the subjective weight value set in step S04 are determined to be reasonable;
step S09, repeating the steps S04-S08, re-determining the subjective weight value set of the step S04 each time, forming the subjective weight values judged to be consistent in the step S08 into subjective weight value intervals, and then determining a subjective weight value set corresponding to the evaluation index set;
or the like, or, alternatively,
step S08, judging that the scoring result in the step S07 is consistent with the evaluation result in the evaluation case, and determining that the empirical factor for calculating the comprehensive weight value in the step S06 is reasonable;
step S09, repeating the steps S04-S08, re-determining the empirical factors for calculating the comprehensive weight values in the step S06 each time of repetition, and forming the empirical factor value intervals by the empirical factors judged to be consistent in the step S08
Preferably, the method further comprises:
step S10, selecting the subjective weight value of each evaluation index from the subjective weight value interval determined in the step S09, determining the experience factor of each evaluation index, and scoring the data matrix in the step S02 in the steps S04-S07 to finally obtain the score of the target system;
or the like, or, alternatively,
and S10, determining the subjective weight value of each evaluation index, selecting the experience factor of each evaluation index from the experience factor value interval determined in the step S09, scoring the data matrix in the step S02 in the steps S04-S07, and finally obtaining the score of the target system.
Preferably, the step S07 includes: the score of the target system is given by the following formula:
wherein S isjScore for jth target System, sijThe score of the ith index of the jth target system is obtained.
The invention has the following beneficial effects:
an electrochemical energy storage system evaluation method for guiding bid inviting purchase can comprehensively evaluate an electrochemical energy storage system by combining subjective and objective factors, is accurate and efficient in evaluation, and is beneficial to selecting a proper electrochemical energy storage system from a plurality of electrochemical energy storage systems during bid inviting.
Drawings
FIG. 1 is a flow chart of an electrochemical energy storage system evaluation method for instructional bidding procurement in accordance with the invention;
FIG. 2 is a chart showing the scoring results of the first embodiment;
FIG. 3 is a chart showing the final scoring results of the first embodiment; the subjective weight value and the experience factor are reasonable values obtained after multiple detections;
FIG. 4 is a chart showing the scoring results of the second step S07 according to the embodiment;
fig. 5 shows a scoring result chart of the two steps S10 of the embodiment.
Detailed Description
The following are specific embodiments of the present invention and are further described with reference to the drawings, but the present invention is not limited to these embodiments.
Referring to fig. 1, an electrochemical energy storage system evaluation method for guiding bid procurement is characterized by comprising the following steps:
step S01, obtaining evaluation index sets of a plurality of target systems;
step S02, acquiring a data matrix of the evaluation index corresponding to the target system based on the evaluation index set;
step S03, obtaining an evaluation case of the known electrochemical energy storage system, wherein the evaluation case comprises an evaluation result of the electrochemical energy storage system;
step S04, determining a subjective weight value set corresponding to the evaluation index set;
step S05, determining an objective weight value set corresponding to the evaluation index set according to the evaluation case and the data matrix;
step S06, calculating a comprehensive weight value of the evaluation index according to the subjective weight value in the subjective weight value set and the objective weight value in the objective weight value set;
and step S07, calculating the score of the target system according to the comprehensive weight value of the evaluation index.
In step S01, the target system refers to the electrochemical energy storage system to be evaluated. Generally, a system meeting the requirement needs to be selected from a plurality of electrochemical energy storage systems in the bidding process. The target system can be a lead-acid battery system, a lithium ion battery system, a nickel-hydrogen battery system, a zinc-air battery system, a sodium-sulfur battery system, an all-vanadium redox flow battery system, a zinc-nickel battery system and the like. Acquiring a plurality of target systems refers to acquiring two or more target systems. The evaluation index set is { energy efficiency, energy density, power density, nominal voltage, cycle number, self-discharge rate, kilowatt-hour cost, environmental factor, safety, minimum working temperature and discharge depth }.
In step S02, the data matrix is used for multi-index weight determination and comprehensive evaluation of the electrochemical energy storage system. The data in the data matrix is the index parameter or the index parameter score. Specifically, the data matrix includes a target system, an evaluation index, and data (e.g., index parameters) of the target system corresponding to the evaluation index.
In step S03, it is known that electrochemical energy storage system evaluation cases are established based on the electrochemical energy storage system cases obtained through historical bidding, and the situations of the electrochemical energy storage system application obtained through the historical bidding are summarized. The evaluation case comprises evaluation results of the electrochemical energy storage system, and mainly reflects relative merits of each system, particularly merits of each system in each scene, and influence importance of different evaluation indexes on each system in each scene.
The step S04 includes: according to the application requirements of the energy storage system and the evaluation results in the evaluation cases, different evaluation indexes are ranked from high to low according to the importance degree, and a subjective weight value set with the sum of 1 is set according to the ranking. For example, when the electrochemical energy storage system is applied to peak clipping and valley filling, it can be known from the evaluation case that the factors of energy efficiency, cycle number, safety, electricity consumption cost, environmental effect, etc. of the battery technology need to be focused under the current application requirements. Therefore, various evaluation indexes can be ranked from high to low according to importance degree, and the evaluation indexes are as follows in sequence: safety, environmental factors, cycle times, cost of electricity, energy efficiency, energy density, nominal voltage, power density, self-discharge rate. And then, determining the subjective weight value of each evaluation index according to the ratio of the importance.
The method of the invention also comprises the following steps:
step S08, judging that the scoring result in the step S07 is consistent with the evaluation result in the evaluation case, and determining the subjective weight value in the subjective weight value set in the step S04 to be reasonable;
and S09, repeating the steps S04-S08, re-determining the subjective weight value set of the step S04 each time, forming the subjective weight values judged to be consistent in the step S08 into subjective weight value intervals, and then determining a subjective weight value set corresponding to the evaluation index set.
When the electrochemical energy storage system is evaluated for the first time, the subjective weight values of the evaluation indexes can be sorted and preset according to the importance degrees according to historical data in the evaluation cases. After the evaluation process of steps S01-S07 is executed, verifying whether the scoring result is consistent with the evaluation result in the evaluation case, if not, adjusting the subjective weight value until the scoring result is consistent with the evaluation result in the evaluation case; if the subjective weight values are consistent, the preset subjective weight values are reasonable. After the evaluation result is judged to be consistent or inconsistent with the evaluation result in the evaluation case, step S09 can be executed, and a reasonable subjective weight value interval can be obtained through multiple judgments for other evaluation electrochemical energy storage systems during bidding purchase.
The subjective weight values of the scoring results which are consistent with the evaluation results in the evaluation cases can be verified through the step S09, then the subjective weight value intervals of each index evaluation are obtained, and the subjective weight value intervals of all index evaluations form a subjective weight value set.
The step S05 includes:
step S51, discretizing the data matrix;
step S52, calculating the indistinguishable relation of the evaluation index set by using the rough set principle from the data matrix after the discretization processing, and calculating the importance set of the evaluation index set;
and step S53, determining an objective weight value set corresponding to the evaluation index set according to the importance set.
In step S51, the electrochemical energy storage system corresponding to the application requirement in the history case is determined from the evaluation case, and then the relevant data is extracted from the data matrix, and a part of the data matrix, that is, the sub-data matrix corresponding to the evaluation index of the relevant electrochemical energy storage system, is mainly extracted.
The discretization processing method of the step S51 is one of the following two methods:
the condition discretization method comprises the following steps: and contrasting the evaluation index score reference table, converting the data of the subdata matrix into scores, and obtaining the subdata matrix with discretized conditions. The evaluation index scoring reference table can be a scoring guide and the like, for example, scoring is performed in a percentage system according to the evaluation index scoring criterion of the electrochemical energy storage system suitable for peak clipping and valley filling. The method can perform condition classification on the data of each evaluation index in the sub-data matrix to obtain a condition discretization matrix.
Two-stage discretization method: scoring the data of the sub-data matrix, wherein the maximum value of the parameter of the ith index is full score, the minimum value of the parameter of the ith index is zero score, and the rest parameters of the ith index are distributed between the zero score and the full score according to the proportion; and taking the data average value of each evaluation index in the sub-data matrix after grading as a boundary, and classifying the data of the evaluation index into two grades to obtain a two-grade discretization matrix.
The calculation of the unresolvable relationship in the step S52 specifically includes: for each two electrochemical energy storage systems, the evaluation index sets are completely the same, and the electrochemical energy storage systems can be determined to be indistinguishable. If the evaluation index sets of every two electrochemical energy storage systems are not completely the same, the two electrochemical energy storage systems can be identified.
When the condition discretization method is adopted in step S51, the importance sig ({ c) of each evaluation index of the importance set in step S52i}) is calculated according to the following formula:
wherein, U is the set of all data under the evaluation index, PkIs the set of k-th grades under the evaluation index, and m is the total number of grades of the evaluation index.
When the two-stage discretization method is adopted in the step S51, the stepImportance sig ({ c) of each evaluation index of the importance set in S52i}) is equal to the number U of the energy storage systems which can be distinguished after the two-stage discretization matrix deletes the data of the evaluation indexi。
The step S53 includes calculating an objective weight value of each evaluation index according to the following formula:
。
the step S06 includes: the determination of the comprehensive weight value of the evaluation index is obtained by the following formula:
wherein ω isiIs the integral weight value, omega, of the ith indexsiAnd ωoiThe subjective weight value and the objective weight value of the ith index are respectively, and f is an experience factor.
The empirical factor is preset empirically when the electrochemical energy storage system is evaluated for the first time. After the first scoring is finished, judging that the scoring result in the step S07 is consistent with the evaluation result in the evaluation case, and determining that the empirical factor for calculating the comprehensive weight value is reasonable in the step S06; if the evaluation result is not reasonable, the experience factor needs to be adjusted until the evaluation result is consistent with the evaluation result in the evaluation case.
The invention can also repeat the steps of S04-S07 and the step of judging whether the scoring result in the step S07 is consistent with the evaluation result in the evaluation case, the empirical factor for calculating the comprehensive weight value in the step S06 is re-determined every time the steps are repeated, and the empirical factor which is judged to be consistent forms an empirical factor value-taking interval. After the evaluation result is judged to be consistent or inconsistent with the evaluation result in the evaluation case, the process of repeatedly determining the experience factor and the experience factor value interval last time can be executed, and a reasonable experience factor value interval can be obtained through multiple judgments, so that a reasonable value range selection is provided for bidding, or the evaluation electrochemical energy storage system is used for other bidding purchasing.
In another embodiment, the method further comprises:
step S08, judging that the scoring result in the step S07 is consistent with the evaluation result in the evaluation case, and determining that the empirical factor for calculating the comprehensive weight value in the step S06 is reasonable;
and S09, repeating the steps S04-S08, re-determining the empirical factors of the step S06 for calculating the comprehensive weight value each time, and forming an empirical factor value interval by the empirical factors which are judged to be consistent in the step S08.
In another embodiment, the present invention may further combine the above processes of determining the value interval of the empirical factor and determining the subjective weight value interval, and repeatedly determine and determine the value interval.
The method of the present invention can be evaluated once through the steps S01-S07. Or, the method further includes step S10, based on selecting the subjective weight value of each evaluation index and the experience factor determined empirically from the subjective weight value interval determined in steps S08 and S09, or based on selecting the subjective weight value of each evaluation index and the experience factor of each evaluation index from the experience factor value interval determined in steps S08 and S09, or based on selecting the subjective weight value of each evaluation index from the subjective weight value interval determined in steps S08 and S09 and selecting the experience factor from the experience factor value interval determined in steps S08 and S09, scoring of steps S04-S07 is performed on the data matrix in step S02, and finally, the scoring of all electrochemical energy storage systems is obtained.
When the evaluation is carried out for one time, the subjective weight value and/or the empirical factor value is determined based on experience, or the subjective weight value and/or the empirical factor value is selected and determined from a reasonable subjective weight value interval and/or an empirical factor value interval obtained from history.
When the evaluation including the step S10 is performed, before a reasonable subjective weight value interval and/or an empirical factor value interval are not obtained, the above steps may be performed on all electrochemical energy storage systems to be bid to obtain an evaluation result, the rationality of the evaluation result is compared, and the reasonable subjective weight value interval and/or the empirical factor value interval is determined. Or before a reasonable subjective weight value interval and/or an empirical factor value interval are not obtained, the steps can be carried out on part of the electrochemical energy storage system to be targeted, an evaluation result is obtained, the rationality of the evaluation result is compared, and the reasonable subjective weight value interval and/or the empirical factor value interval are determined. Once a reasonable interval is obtained through one of the above embodiments, a reasonable subjective weight value and an empirical factor are selected, and all electrochemical energy storage systems for bidding are finally evaluated so as to facilitate bidding. In the latter real-time mode, before step S51, the method further includes: extracting a sub data matrix of the corresponding evaluation index of the relevant electrochemical energy storage system from the data matrix according to the application requirement of the energy storage system and the electrochemical energy storage system related to the application requirement in the evaluation case; and S51-S53 are used for carrying out discretization processing on the sub-data matrix, calculating an indistinguishable relation, and calculating an importance set and an objective weight value set of the evaluation index set.
The step S07 includes: the score of the target system is given by the following formula:
wherein S isjScore for jth target System, sijThe score of the ith index of the jth target system is obtained.
Example one
In the embodiment, a condition discretization method is adopted, and each index parameter is scored by taking an evaluation index scoring reference table as a reference.
In step S01, a set of evaluation indexes of a plurality of target systems is obtained.
Given that the evaluation required at this time is the evaluation of seven batteries including a lead-acid battery, a lithium ion battery, a nickel-metal hydride battery, a zinc-air battery, a sodium-sulfur battery, an all-vanadium redox flow battery and a zinc-nickel battery for peak clipping and valley filling under 11 evaluation indexes including energy efficiency, energy density, power density, nominal voltage, cycle times, self-discharge rate, power consumption cost, environmental factors, safety, lowest working temperature and discharge depth, and the evaluation is used as a selection reference for the energy storage system during time putting.
Step S02, based on the evaluation index set, obtain a data matrix of the evaluation index corresponding to the target system, see table one below.
Table one: data matrix
The data in the data matrix is provided by a tenderer, and part of the evaluation indexes in the first table are value ranges which comprise possible values of all batteries of the same type on the market. While the value provided by the tenderer is generally constant. The calculation in the present example of the invention is based on a constant value calculation, for example, the constant value in the present example is selected as the median of the above-mentioned value range.
And step S03, obtaining an evaluation case of the known electrochemical energy storage system, wherein the evaluation case comprises an evaluation result of the electrochemical energy storage system. According to the lead-acid battery, the zinc-air battery and the lithium ion battery application cases obtained by historical bidding, the lithium ion battery is superior to the lead-acid battery and superior to the zinc-air battery in the application scene of peak clipping and valley filling, and the value of the subjective weight can be determined according to the result.
And step S04, determining the subjective weight value set corresponding to the evaluation index set. The electrochemical energy storage system applied to peak clipping and valley filling focuses on factors such as energy efficiency, cycle frequency, safety, kilowatt-hour cost, environmental effect and the like of a battery technology, and the importance of performance indexes is sequentially from high to low: safety, environmental factors, cycle times, cost of electricity, energy efficiency, energy density, nominal voltage, power density, self-discharge rate. And according to the ranking of the importance degrees, preliminarily drawing subjective weight values as shown in the following table II.
Subjective weight value table of various evaluation indexes of table two
Step S05 determines the objective weight value set corresponding to the evaluation index set. Firstly, the data of the lead-acid battery, the zinc-air battery and the lithium ion battery related to the electrochemical energy storage system evaluation case known in the step S03 are extracted from the data matrix of the step S02 as shown in the following table III:
table three: subdata matrix
In this embodiment, a part of systems in the target system is evaluated first, that is, a part of data matrices of the data matrix in step S02 is obtained as sub-data matrices to perform subsequent step calculation, and then a subjective weight value set and an empirical factor value interval corresponding to the evaluation index set in step S09 are obtained. The method is not limited to the preliminary evaluation of a part of the system to obtain a reasonable subjective weight value interval and an experience factor value interval; the invention can also perform preliminary evaluation on all target systems.
And assigning the table according to 'evaluation index assigning criterion suitable for the electrochemical energy storage system for peak clipping and valley filling' to obtain the following table four.
Table four: rating table of subdata matrix
The importance of each evaluation index is obtained from the following formula:
wherein, U is the set of all data under the evaluation index, PkIs the set of k-th grades under the evaluation index, and m is the total number of grades of the evaluation index.
For energy efficiency, for example, U = 3. There are a total of three grades 60, 90, 100, so m = 3. When k =1, there are 1 in 60 grades, Pk= 1; when k =2, there are 1 in 90 grades, Pk= 1; when k =3, 100 are graded by 1, Pk=1。sig=1*（3-1）+1*（3-1）+1*（3-1）=6。
Take the security score as an example, U = 3. There are 60, 75 two fractions, so m = 2. When k =1, 1 is classified into 60 grades, and Pk = 1; when k =2, there are 2 75 ranks, and Pk = 2. sig =1 (3-1) +2 (3-2) = 4. In the above manner, the calculated importance is as follows:
table five: importance table of evaluation index
The objective weight of each evaluation index is obtained by the following formula:
calculating to obtain the objective weight value as the following table six:
table six: objective weight value table of evaluation index
Step S06, calculating the comprehensive weight value of the evaluation index according to each subjective weight value in the subjective weight value set and the objective weight value in the objective weight value set:
wherein ω isiIs the integrated weight, ω, of the i-th indexsiAnd ωoiThe subjective weight and the objective weight of the ith index are respectively, and f is an empirical factor.
The empirical factor is preliminarily determined to be 0.3, and the comprehensive weight value calculated by the formula is as follows:
TABLE VII: comprehensive weight value table of evaluation index
Step S07, calculating the score of the target electrochemical energy storage system according to the comprehensive weight value of each evaluation index in a weighted manner, wherein the specific formula is as follows:
wherein S isjThe score for the jth target electrochemical energy storage system is given. The scoring results obtained are shown in FIG. 2 below.
And step S08, judging that the obtained scoring result meets the condition that the lithium ion battery is superior to the lead-acid battery and the zinc-air battery in the step S03, and proving that the value of the subjective weight in the step S04 and the value of the test factor in the step S06 are reasonable.
Step S09, repeating steps S04 to S09, changing the values of the subjective weight and the empirical factor, and obtaining the following table eight of reasonable values of the subjective weight and the empirical factor:
table eight: weight value interval of evaluation index and value interval table of experience factor
In step S10, the data matrix in step S02 is scored according to the same principle as in steps S04 to S07 by using the index weight and the empirical factor determined in step S09, and the scoring result is obtained as shown in fig. 3 below. For example, when applied to an electrochemical energy storage system for peak clipping and valley filling, the weighted value of energy efficiency is 0.07, the weighted value of energy density is 0.05, the weighted value of power density is 0.02, the weighted value of nominal voltage is 0.02, the weighted value of cycle number is 0.13, the weighted value of self-discharge rate is 0.01, the weighted value of safety is 0.3, the weighted value of environmental factor is 0.2, the weighted value of kilowatt-hour cost is 0.1, and the empirical factor is 0.3. The selection of the values conforms to the importance ranking of the second table. Different weight values are determined according to bidding application scenarios. Evaluation results were obtained: in the evaluation of the 7 types of batteries, the all-vanadium redox flow battery is the most suitable electrochemical energy storage system for peak clipping and valley filling, the performance data of the seven batteries are obtained when bidding is carried out, and the all-vanadium redox flow battery is recommended to be selected for purchase.
Example two
In the two-stage discretization adopted in the second discretization, the scoring method for each index is that the maximum value of the parameter of the ith index is full score and the minimum value is zero score, and other parameters are proportionally distributed between the zero score and the full score.
In step S01, a set of evaluation indexes of a plurality of target systems is obtained.
Given that the evaluation required at this time is the evaluation of seven batteries including a lead-acid battery, a lithium ion battery, a nickel-metal hydride battery, a zinc-air battery, a sodium-sulfur battery, an all-vanadium redox flow battery and a zinc-nickel battery for peak clipping and valley filling under 11 evaluation indexes including energy efficiency, energy density, power density, nominal voltage, cycle times, self-discharge rate, power consumption cost, environmental factors, safety, lowest working temperature and discharge depth, and the evaluation is used as a selection reference for the energy storage system during time putting.
Step S02, based on the evaluation index set, obtain a data matrix of the evaluation index corresponding to the target system, see table one.
The data in the data matrix is provided by a tenderer, and part of the evaluation indexes in the first table are value ranges which comprise possible values of all batteries of the same type on the market. While the value provided by the tenderer is generally constant. The calculation in the present example of the invention is based on a constant value calculation, for example, the constant value in the present example is selected as the median of the above-mentioned value range.
And step S03, obtaining an evaluation case of the known electrochemical energy storage system, wherein the evaluation case comprises an evaluation result of the electrochemical energy storage system. According to the lead-acid battery, the zinc-air battery and the lithium ion battery application cases obtained by historical bidding, the lithium ion battery is superior to the lead-acid battery and superior to the zinc-air battery in the application scene of peak clipping and valley filling, and the value of the subjective weight can be determined according to the result.
And step S04, determining the subjective weight value set corresponding to the evaluation index set. The electrochemical energy storage system applied to peak clipping and valley filling focuses on factors such as energy efficiency, cycle frequency, safety, kilowatt-hour cost, environmental effect and the like of a battery technology, and the importance of performance indexes is sequentially from high to low: safety, environmental factors, cycle times, cost of electricity, energy efficiency, energy density, nominal voltage, power density, self-discharge rate. And according to the ranking of the importance degrees, preliminarily drawing subjective weight values as shown in a table II.
Step S05 determines the objective weight value set corresponding to the evaluation index set. Firstly, data of the lead-acid battery, the zinc-air battery and the lithium ion battery related to the electrochemical energy storage system evaluation case known in the step S03 are extracted from the data matrix of the step S02, and are shown in table three.
In this embodiment, a part of systems in the target system is evaluated first, that is, a part of data matrices of the data matrix in step S02 is obtained as sub-data matrices to perform subsequent step calculation, and then a subjective weight value set and an empirical factor value interval corresponding to the evaluation index set in step S09 are obtained. The method is not limited to the preliminary evaluation of a part of the system to obtain a reasonable subjective weight value interval and an experience factor value interval; the invention can also perform preliminary evaluation on all target systems.
Taking the maximum value of the parameter of the ith evaluation index as a full score and the minimum value as a zero score, and distributing the rest parameters between the zero score and the full score according to the proportion to obtain the single parameter scores of the three energy storage systems as shown in the following table nine:
table nine: rating table of subdata matrix
Taking energy efficiency as an example, the lead-acid battery, the lithium ion battery and the zinc-air battery in the third table are 82.5, 94 and 62.5 in sequence. 94 is the maximum value, the energy efficiency score of the lithium ion battery is 100; 62.5 is the minimum value, the energy efficiency score of the zinc-air cell is 0; the score of the lead-acid battery is converted into (82.5-62.5)/(94-62.5) × 100% ≈ 63.5 based on the above score.
Taking the data average value of each evaluation index in the data matrix as a boundary, classifying the evaluation index data into two levels, and obtaining a two-level discretization matrix as shown in the following table ten, wherein the table ten shows the indistinguishable relation of an evaluation index set, for example, the evaluation index set of a lead-acid energy storage system is { 101001001 }; the evaluation index of the lithium ion energy storage system is { 1011110100 }, and the evaluation index can be considered to be distinguishable.
TABLE Ten: two-stage discretization table of subdata matrix
Importance of evaluation index of i-th type sig ({ c)i}) is equal to the number U of the energy storage systems which can be distinguished after the index data is deleted by the matrix of two-stage discretizationi. Specifically, the 1 st evaluation index, that is, the column in table nine where the energy efficiency is located, is deleted first, and then a new evaluation table is obtained. And after the new grading table is subjected to two-stage discretization processing, a new two-stage discretization table with the energy efficiency deleted in the table ten is obtained. If the evaluation indexes of the three energy storage systems obtained from the new two-stage discretization table are not completely equal, the three energy storage systems are considered to be distinguishable, and the importance of the energy efficiency is 3/3= 1. If only two of the three energy storage systems are resolvable, the importance of energy efficiency is 2/3 ≈ 0.7. In this way, the ith evaluation index is deleted, a new scoring table and a new two-level discretization table are obtained, and then the importance of the ith evaluation index is obtained. Finally, the importance obtained is as follows in table eleven:
table eleven: importance table of evaluation index
The objective weight of each evaluation index is obtained by the following formula:
the objective weight values are calculated as the following twelve:
table twelve: objective weight value table of evaluation index
Step S06: calculating a comprehensive weight value of the evaluation index according to each subjective weight value in the subjective weight value set and an objective weight value in the objective weight value set:
wherein ω isiIs the integrated weight, ω, of the i-th indexsiAnd ωoiThe subjective weight and the objective weight of the ith index are respectively, and f is an empirical factor.
The empirical factor is initially intended to be 0.3, and the combined weight values calculated by the above formula are as follows:
table thirteen: comprehensive weight value table of evaluation index
Step S07: and calculating the score of the target electrochemical energy storage system according to the comprehensive weight value of each evaluation index in a weighted manner, wherein the specific formula is as follows:
wherein Sj is the score of the jth target electrochemical energy storage system. The scoring results obtained are shown in FIG. 4 below.
Step S08: and judging that the obtained scoring result meets the condition that the lithium ion battery is superior to the lead-acid battery and the zinc-air battery in the step S03, and proving that the value of the subjective weight in the step S04 and the value of the test factor in the step S06 are reasonable.
Step S09: repeating the steps S04 to S09, changing the values of the subjective weight and the experience factor, and obtaining the reasonable values of the subjective weight and the experience factor as follows:
table fourteen: weight value interval of evaluation index and value interval table of experience factor
Step S10: the data matrix in step S02 is scored on the same principle as in steps S04 to S08 using the evaluation index weight and the empirical factor determined in step S10, and the scoring result is obtained as shown in fig. 5 below.
For example, when applied to an electrochemical energy storage system for peak clipping and valley filling, the weighted value of energy efficiency is 0.07, the weighted value of energy density is 0.05, the weighted value of power density is 0.02, the weighted value of nominal voltage is 0.02, the weighted value of cycle number is 0.13, the weighted value of self-discharge rate is 0.01, the weighted value of safety is 0.3, the weighted value of environmental factor is 0.2, the weighted value of kilowatt-hour cost is 0.1, and the empirical factor is 0.3. The selection of the values conforms to the importance ranking of the second table. Different weight values are determined according to bidding application scenarios.
Evaluation results were obtained: in the evaluation of the 7 types of batteries, the zinc-nickel battery is the most suitable electrochemical energy storage system for peak clipping and valley filling, the performance data of the seven batteries are obtained when bidding is carried out, and the zinc-nickel battery is recommended to be selected for purchase.
It will be appreciated by persons skilled in the art that the embodiments of the invention described above and shown in the drawings are given by way of example only and are not limiting of the invention. The objects of the present invention have been fully and effectively accomplished. The functional and structural principles of the present invention have been shown and described in the examples, and any variations or modifications of the embodiments of the present invention may be made without departing from the principles.
Claims (10)
1. An electrochemical energy storage system evaluation method for guiding tender procurement is characterized by comprising the following steps:
step S01, obtaining evaluation index sets of a plurality of target systems;
step S02, acquiring a data matrix of the evaluation index corresponding to the target system based on the evaluation index set;
step S03, obtaining an evaluation case of the known electrochemical energy storage system, wherein the evaluation case comprises an evaluation result of the electrochemical energy storage system;
step S04, determining a subjective weight value set corresponding to the evaluation index set;
step S05, determining an objective weight value set corresponding to the evaluation index set;
step S06, calculating a comprehensive weight value of the evaluation index according to the subjective weight value in the subjective weight value set and the objective weight value in the objective weight value set;
and step S07, calculating the score of the target system according to the comprehensive weight value of the evaluation index.
2. The method as claimed in claim 1, wherein the step S04 comprises: according to the application requirements of the energy storage system and the evaluation results in the evaluation cases, different evaluation indexes are ranked from high to low according to the importance degree, and a subjective weight value set with the sum of 1 is set according to the ranking.
3. The method as claimed in claim 1, wherein the step S05 comprises:
step S51, discretizing the data matrix;
step S52, calculating the indistinguishable relation of the evaluation index set by using the rough set principle from the data matrix after the discretization processing, and calculating the importance set of the evaluation index set;
and step S53, determining an objective weight value set corresponding to the evaluation index set according to the importance set.
4. The method as claimed in claim 3, wherein the discretization processing method of step S51 is one of the following two methods: the condition discretization method comprises the following steps: comparing the evaluation index score reference table, converting the data of the data matrix into scores, and obtaining a condition discretization data matrix;
two-stage discretization method: scoring data of the data matrix, wherein the maximum value of the parameter of the ith index is full score, the minimum value of the parameter of the ith index is zero score, and the rest parameters of the ith index are distributed between the zero score and the full score according to the proportion; and taking the average value of the data of each evaluation index in the scored data matrix as a boundary, classifying the data of the evaluation index into two grades, and obtaining a two-stage discretization matrix.
5. The method of claim 4, wherein the evaluation method of electrochemical energy storage system for guiding tender purchasing,
when the condition discretization method is adopted in step S51, the importance sig ({ c) of each evaluation index of the importance set in step S52i}) is calculated according to the following formula:
wherein, U is the set of all data under the evaluation index, PkThe evaluation index is a set of k grades under the evaluation index, and m is the total number of the grades of the evaluation index;
when the two-stage discretization method is adopted in step S51, the importance sig ({ c) of each evaluation index of the importance set in step S52i}) is equal to the number U of the energy storage systems which can be distinguished after the two-stage discretization matrix deletes the data of the evaluation indexi。
6. The method as claimed in claim 3, wherein the step S53 includes calculating the objective weight value of each evaluation index according to the following formula:
7. the method as claimed in claim 1, wherein the step S06 comprises: the determination of the comprehensive weight value of the evaluation index is obtained by the following formula:
wherein ω isiIs the integral weight value, omega, of the ith indexsiAnd ωoiThe subjective weight value and the objective weight value of the ith index are respectively, and f is an experience factor.
8. The method of claim 1, wherein the method further comprises:
step S08, judging that the scoring result in the step S07 is consistent with the evaluation result in the evaluation case, and determining the subjective weight value in the subjective weight value set in the step S04 to be reasonable;
step S09, repeating the steps S04-S08, re-determining the subjective weight value set of the step S04 each time, forming the subjective weight values judged to be consistent in the step S08 into subjective weight value intervals, and then determining a subjective weight value set corresponding to the evaluation index set;
or the like, or, alternatively,
step S08, judging that the scoring result in the step S07 is consistent with the evaluation result in the evaluation case, and determining that the empirical factor for calculating the comprehensive weight value in the step S06 is reasonable;
and S09, repeating the steps S04-S08, re-determining the empirical factors for calculating the comprehensive weight values in the step S06 each time of repetition, and forming an empirical factor value interval by the empirical factors which are judged to be consistent in the step S08.
9. The method of claim 8, wherein the method further comprises:
step S10, selecting the subjective weight value of each evaluation index from the subjective weight value interval determined in the step S09, determining the experience factor of each evaluation index, and scoring the data matrix in the step S02 in the steps S04-S07 to finally obtain the score of the target system;
or the like, or, alternatively,
and S10, determining the subjective weight value of each evaluation index, selecting the experience factor of each evaluation index from the experience factor value interval determined in the step S09, scoring the data matrix in the step S02 in the steps S04-S07, and finally obtaining the score of the target system.
10. The method as claimed in claim 1, wherein the step S07 comprises: the score of the target system is given by the following formula:
wherein S isjScore for jth target System, sijThe score of the ith index of the jth target system is obtained.
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