CN113657739A - Method for evaluating quantitative energy storage under multiple scenes - Google Patents
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Abstract
The invention discloses a quantitative energy storage evaluation method under multiple scenes, which starts from four indexes, namely an economic index, a technical performance index, an environmental impact index and a power grid related index. Firstly, establishing an evaluation index of energy storage; secondly, standardizing the score by adopting a z-score standardization method; then, selecting weights by adopting a matrix judging method; and finally, obtaining the energy storage score condition under the current scene. The invention aims to select the factors which need to be considered for the specific type of energy storage under a specific scene, and the energy storage system which is better in performance under the scene can be selected according to the requirement by the evaluation method. The method has comprehensive selected energy storage evaluation indexes, and evaluates the application of the energy storage system in a specific scene through a multi-dimensional and multi-target evaluation system.
Description
Technical Field
The invention belongs to the field of energy storage application evaluation, and particularly relates to a quantitative energy storage evaluation method under multiple scenes.
Background
With the large amount of grid connection of new energy power generation forms such as wind power, photovoltaic and the like, the uncertainty of a power grid is increased. The energy storage system is matched with renewable energy power generation, so that the output of wind power, photovoltaic and the like can be flexibly regulated, and the problem of power grid caused by randomness, volatility and intermittency is solved, so that the importance of the energy storage system in a power system is increasingly improved. However, the performance of various types of power storage in the aspects of indexes such as economy, technology and environmental influence is different, and the selection of which type of power storage needs to be considered in a specific scene has a plurality of factors, which is often a problem with strong subjectivity. Therefore, it is necessary to provide a method for quantitatively evaluating the applicability of energy storage.
The method for evaluating the economic efficiency of the energy storage technology is comprehensively reviewed by research, and the cost benefit is analyzed through energy storage benefit evaluation software, but the performance of the energy storage outside the economic efficiency is not considered. A comprehensive evaluation index system comprising economy, system reliability and load smoothness is established by research and can be used for evaluation and comparison of various schemes. An evaluation index system of the light storage combined power generation system is provided. The prior art evaluates one or more aspects, and a comprehensive evaluation system is not established. In some researches, a comprehensive evaluation index system is arranged, the weight is selected by adopting a judgment matrix method, but the stored energy is scored according to empirical values, so that the subjectivity is high, and the calculation and derivation of each index are lacked.
Disclosure of Invention
The invention aims to provide a method for quantitatively evaluating energy storage under multiple scenes aiming at the defects of the prior art.
The purpose of the invention is realized by the following technical scheme: a method for evaluating quantitative energy storage under multiple scenes comprises the following steps:
(1) and establishing an evaluation index of the stored energy.
(2) The scores were normalized using the z-score normalization method.
(3) And selecting the weight by adopting a matrix judgment method according to different scenes.
(4) And obtaining the energy storage score condition under the current scene.
Further, the step (1) comprises the following steps:
(a) and selecting evaluation indexes, wherein the selected indexes are divided into four categories, namely economic indexes, technical performance indexes, environmental impact indexes and indexes related to a power grid. The economic indexes comprise daily cost of energy storage, real-time electric quantity benefit of the energy storage and daily standby power benefit; the technical performance indexes comprise energy storage life and cycle times; the environmental impact indexes comprise unit capacity carbon dioxide emission and unit capacity land occupation area; the indexes related to the power grid comprise the indexes of delaying the upgrading benefit of the power grid, equivalent load standard deviation and reliability.
(b) And obtaining evaluation index data. The energy storage service life, the carbon dioxide emission amount per unit volume and the land occupation area per unit volume are obtained through basic data provided by an energy storage factory, and calculation is not needed. The rest indexes need to be obtained through calculation.
Further, in step (b), the index obtained by calculation includes:
(1) calculation of economic indicators
The daily cost calculation method for energy storage comprises the following steps:
in the formula: cpUnit power cost for stored energy; cECost per capacity for stored energy; prRated power for stored energy; erRated capacity for stored energy; d is the energy storage life; r is the discount rate; cfDaily operation and maintenance cost of unit energy for energy storage; ps is a force output value at each moment of energy storage, and according to a power supply convention, Ps is positive during energy storage discharge and is negative during charging; t is the total scheduling time number; Δ t is the scheduling time interval.
The real-time electric quantity benefit of the stored energy is that the stored energy is charged when the electricity price is low, the stored energy is discharged when the electricity price is high, the obtained price difference profit is obtained, and the calculation formula is as follows:
in the formula: celcThe electricity prices at each time.
The reserve power of energy storage refers to the up-down adjustable allowance of the energy storage power between the maximum and minimum charge-discharge power, and the reserve power can be used as the reserve power of a power grid, and the obtained benefit is the reserve power benefit of the energy storage. The term "up-regulation" means that the discharge amount of stored energy increases or the charge amount decreases, and the term "down-regulation" means that the discharge amount of stored energy increases or the charge amount decreases. The formula for the daily reserve power gain is then:
in the formula: a. theuFor up-regulation of the subsidy price, AdFor lowering the subsidy price.
(2) Calculation of technical performance indicators
The number of cycles of energy storage is related to the depth of discharge, the higher the depth of charge and discharge, the fewer the number of cycles of the battery. And adopting 0.2C multiplying power, and obtaining a calculation formula of the cycle number of the battery by fitting, wherein the calculation formula is as follows:
N0.2c＝3946×(Dod)-1.58 (6)
in the formula: dod is the Depth of discharge (Depth of discharge) of the stored energy.
(3) Grid-related index calculation
The calculation formula of the equivalent load standard deviation is as follows:
Pnetload＝Pload-Pnew (8)
in the formula: pnetloadIs the net load power, P, of the systemloadFor load power, PnewFor new energy output power value, PavIs the average of the payload power.
The calculation formula for delaying the upgrading benefit of the power grid is as follows:
in the formula: ctransThe unit replacement cost for the transformer; pmaxThe maximum value of the load power; tau is the annual load growth rate; Δ M is the postponable upgrading and capacity expanding life of the power grid, and λ is the peak clipping rate of stored energy; clineThe unit cost for line capacity expansion.
Further, in the step (2), the z-score normalized calculation formula is as follows:
in the formula: x is the number ofiIs the original value of the i-th index, yiThe number of the ith index after the normalization processing is shown, n is the number of objects to be compared and corresponds to the number of the energy storage types to be compared, and s is the standard deviation. y isiThe first expression of (a) is a revenue-type metric and the second expression is a cost-type metric. After z-score normalization, 0 represents the mean level, greater than 0 represents greater than the mean level, less than 0 represents less than the mean level, and larger absolute values represent greater or lesser than the mean level.
Further, the step (3) is specifically:
the idea of judging the matrix is to compare the indexes two by two. When n indexes exist, the corresponding judgment matrix is as follows:
after the judgment matrix is filled, the characteristic values of the judgment matrix are calculated, the maximum characteristic value is found, the characteristic vector corresponding to the judgment matrix is calculated, and the corresponding weight relation among the n indexes can be obtained by unitization.
Defining the consistency index CI of the judgment matrix as follows:
in the formula: lambda [ alpha ]maxThe maximum eigenvalue of the judgment matrix is shown, and n is the number of indexes compared. And when the CI is more than or equal to 0 and less than or equal to 0.1, the judgment matrix is considered to pass the consistency check, and otherwise, the judgment matrix is refilled.
Further, the step (4) is specifically as follows:
and multiplying and summing the normalized numerical value of the energy storage index and the corresponding index to obtain the final score of the energy storage. And comparing the final total scores of all types of energy storage, wherein the higher score represents the more suitable score for the current scene.
Further, the reliability index is that after the failure rate of the given equipment is given, the expected value of the system power shortage in one day is calculated by adopting Monte Carlo simulation.
Further, the new energy output power value PnewIncluding photovoltaic output values, fan output values, and the like.
The invention has the beneficial effects that:
(1) the invention aims to select the factors to be considered for the specific type of energy storage under a specific scene, and the energy storage system with better performance under the scene can be selected according to the requirement by the evaluation method;
(2) the method has comprehensive selected energy storage evaluation indexes, and evaluates the application of the energy storage system in a specific scene through a multi-dimensional and multi-target evaluation system.
Detailed Description
The invention discloses a method for quantitatively evaluating energy storage under multiple scenes, which adopts an analytic hierarchy process to divide evaluation indexes into economic indexes, technical performance indexes, environmental influence indexes and indexes related to a power grid, wherein each category is divided into a plurality of indexes, and a calculation method of each index is provided. In order to avoid high subjectivity, a method of judging a matrix is adopted to determine the weight relation between different indexes. In order to avoid subjectivity during grading, a method of corresponding fixed numerical values to fixed scores is not adopted, a membership function is not adopted for grading, instead, the calculated original data is directly adopted for standardization, the difference between numerical values and dimensions among all indexes is eliminated, and then the total score is calculated according to the calculated weight. Under different scenes, a new score condition can be obtained only by re-filling the judgment matrix and changing the weight relation among different indexes. The invention can obtain the energy storage type most suitable for the current requirement in different scenes.
The invention adopts an Analytic Hierarchy Process (AHP) to evaluate the performance of energy storage. Each index to be evaluated is determined first, and because the numerical values of different indexes are different, the acquired numerical values are subjected to standardization processing. And then according to the requirements of the current scene, calculating appropriate weight through the judgment matrix, finally calculating the final total score of different types of energy storage through the standardized index values and the weights, and selecting the energy storage type most suitable for the current scene according to the score. The method specifically comprises the following steps:
(1) and establishing an evaluation index of the stored energy. The following were used:
(a) and selecting evaluation indexes, wherein the selected indexes are divided into four categories, namely economic indexes, technical performance indexes, environmental impact indexes and indexes related to a power grid. The economic indexes are divided into daily cost of energy storage, real-time electric quantity benefit of energy storage and daily reserve power benefit; the technical performance indexes comprise energy storage life and cycle times; the environmental impact indexes are divided into unit capacity carbon dioxide emission and unit capacity land occupation area; indexes related to the power grid are divided into indexes for delaying the upgrading benefit of the power grid, equivalent load standard deviation and reliability.
(b) And obtaining evaluation index data. The energy storage life, the carbon dioxide emission amount per unit volume and the land occupation area per unit volume in the indexes can be obtained through basic data provided by an energy storage factory without calculation. The other indexes can be obtained only through certain calculation. The calculation method of the remaining indexes will be described below.
(1) Calculation of economic indicators
(1.1) daily cost of energy storage CdayThe calculation method comprises the following steps:
in the formula: cpUnit power cost for stored energy; cECost per capacity for stored energy; prRated power for stored energy; erRated capacity for stored energy; d is the energy storage life; r is the discount rate; cfDaily operation and maintenance cost of unit energy for energy storage; ps is a force output value at each moment of energy storage, and according to a power supply convention, Ps is positive during energy storage discharge and is negative during charging; t is the total scheduling time number; Δ t is the scheduling time interval.
(1.2) real-time electric quantity benefit A of energy storageelcFor energy storage, the energy storage device can be charged at low electricity price and discharged at high electricity price, so that price difference profit can be obtained from the energy storage device, and the calculation formula is as follows:
in the formula: celcThe electricity prices at each time.
And (1.3) the reserve power of the stored energy is the up-down adjustable margin of the stored energy when the stored energy is between the maximum and minimum charge-discharge power, and the reserve power can be used as the reserve power of the power grid, and the obtained benefit is the reserve power benefit of the stored energy. The term "up-regulation" means that the discharge amount of stored energy increases or the charge amount decreases, and the term "down-regulation" means that the discharge amount of stored energy increases or the charge amount decreases. The calculation formula of the up and down standby power is as follows:
Pu＝Pr-Ps (3)
Pd＝Pr+Ps (4)
in the formula: puAnd PdUp standby power and down standby power, respectively.
In engineering, the up-down standby time and the down-up standby time are determined to be calculated according to certain specific indexes, for convenience, the up-down standby time and the down-down standby time are respectively considered to be half, and then the daily standby power gain A is obtainedresThe calculation formula of (2) is as follows:
in the formula: a. theuFor up-regulation of the subsidy price, AdFor lowering the subsidy price.
(2) Calculation of technical performance indicators
The energy storage life can be directly obtained through data provided by a manufacturer. The cycle number of the stored energy is related to the discharge depth, and the higher the charge-discharge depth is, the less the cycle number of the battery is. If the multiplying power of 0.2C is adopted, the cycle number N of the battery is obtained by fitting0.2cThe calculation formula of (2) is as follows:
N0.2c＝3946×(Dod)-1.58 (6)
in the formula: dod is the Depth of discharge (Depth of discharge) of the stored energy.
(3) Grid-related index calculation
The great effect of the stored energy on the power grid is peak clipping and valley filling, so that the peak clipping and valley filling effect of the stored energy is necessary to be considered when the indexes of the stored energy related to the power grid are considered. The invention adopts the equivalent load standard deviation F to measure the effect of energy storage peak clipping and valley filling. The calculation formula is as follows:
Pnetload＝Pload-Pnew (8)
in the formula: pnetloadIs the net load power of the system; ploadIs the load power;newthe new energy output power value can comprise a photovoltaic output value, a fan output value and the like; pavIs the average of the payload power.
In addition, the energy storage system can be equipped to delayThe upgrading of some equipment or lines in the power grid can prolong the service life of the equipment or lines, so that the stored energy has the benefit of delaying the upgrading of the power gridpostAnd the method can also be used as an index related to the power grid. The calculation formula is as follows:
in the formula: ctransUnit replacement costs for the transformer (yuan/KW); pmaxThe maximum value of the load power; τ is the annual load growth rate (%/a); Δ M is the time limit of the power grid upgrading expansion which can be delayed, wherein λ is the peak clipping rate (%) of the stored energy; clineThe unit cost (yuan/KW) for line expansion.
The stored energy may also improve the reliability of the grid. The indexes for measuring the reliability of the Power grid include a system Power shortage Probability time Probability (Loss of Load Probability, LOLP), an Expected Power shortage value (EENS), a system cut-off Power Index (BPECI), an Average Power Availability Index (ASAI), and the like. Scholars have also proposed the concept of "valve stage" and the concept of equipment importance to measure reliability, and have also characterized reliability by sequential monte carlo with reduced loss of power outage, or measured reliability by point estimation. Theoretically, the indexes can be used as evaluation indexes of energy storage for improving the reliability of the system, the invention mainly provides a method for processing and comparing numerical values of multiple indexes, and therefore, for the sake of simplicity, after the failure rate of given equipment, Monte Carlo simulation is adopted to calculate the expected value of system power shortage in one day as the reliability index for measuring the system.
(2) The scores were normalized using the z-score normalization method. The method comprises the following steps:
the invention selects a z-score standardization method, also called standard deviation standardization. The method is characterized in that the average value of the data after standardization is 0, the standard deviation is 1, and even two relatively close numerical values can be different after the z-score standardization, so that the method is suitable for comparison. The formula for z-score normalization is:
in the formula: x is the number ofiIs the original value of the i-th index, yiThe number of the ith index after the normalization processing is shown, n is the number of objects to be compared, corresponding to the number of the energy storage types to be compared in the invention, and s is the standard deviation. y isiThe first expression of (a) is a revenue-type metric and the second expression is a cost-type metric. The profit index is an index having a larger numerical value and the cost index is an index having a smaller numerical value. In the above-mentioned indexes, the real-time electric quantity benefit, the reserve power benefit, the energy storage life, the cycle number and the delay power grid upgrade benefit belong to the benefit type indexes, and the daily cost of energy storage, the unit capacity carbon dioxide emission, the unit capacity land occupation area, the equivalent load standard deviation and the expected value of system electric quantity insufficiency belong to the cost type indexes. After z-score normalization, 0 represents the mean level, greater than 0 represents greater than the mean level, less than 0 represents less than the mean level, and larger absolute values represent greater or lesser than the mean level.
(3) And selecting the weight by adopting a matrix judgment method according to different scenes. The method specifically comprises the following steps:
the requirements are different under different scenes, and the difference is reflected in the selection of the weight. The relevant person selects the appropriate weight according to the requirements of the current scene, but this may cause the weight selection to be sometimes too subjective. In order to avoid the subjectivity, the invention adopts a method of judging a matrix to select the weight. The idea of determining the matrix is to compare the indicators two by two, in other words, one only needs to compare which indicator is important, and does not need to consider which indicator is most important.
Assuming that there are three indexes, the corresponding judgment matrix is:
wherein, the element AijThe meanings of the representatives are shown in Table 1:
table 1: determining the meaning of the matrix elements
| Matrix element Aij | Means for indicating |
| 9 | Index i is more important than index j |
| 7 | Index i is much more important than index j |
| 5 | Index i is more important than index j |
| 3 | Index i is slightly more important than index j |
| 1 | Index i is as important as index j |
| 1/3 | Index i is slightly less important than index j |
| 1/5 | Index i is less important than index j |
| 1/7 | Index i is more secondary than index j |
| 1/9 | Index i is more minor than index j |
| 2,4,6,8 and their inverse | Between the two adjacent judgments |
After the judgment matrix is filled, the corresponding weight relation among the three indexes can be obtained only by calculating the characteristic value of the judgment matrix, finding the maximum characteristic value, calculating the corresponding characteristic vector and conducting unitization.
From the above definition of the elements of the decision matrix, it is obvious that the decision matrix is theoretically a matrix having a main diagonal of 1 and two elements symmetrical about the diagonal being reciprocal to each other. However, when the number of the indicators is large, people tend to forget the previous judgment, so that the judgment matrix is not in the standard form. The method for calculating the weight through the judgment matrix can be used for carrying out compromise when the front and back judgment of people are inconsistent, and the method for obtaining the weight through the judgment matrix can reduce subjectivity and enable the weight to be selected more objectively and reasonably based on the principle. However, it should be noted that sometimes, the difference between the previous and subsequent judgments is too large, and even the importance between the two indexes is opposite when the previous and subsequent judgments are performed, which indicates that there is a problem in the judgment process, so it is necessary to perform consistency check on the filled judgment matrix.
Defining the consistency index CI of the judgment matrix as follows
In the formula: lambda [ alpha ]maxThe maximum eigenvalue of the judgment matrix is shown, and n is the number of indexes compared. And when the CI is more than or equal to 0 and less than or equal to 0.1, the judgment matrix is considered to pass the consistency check, and otherwise, the judgment matrix is refilled.
(4) And obtaining the energy storage score condition under the current scene.
After index normalization and weight calculation are completed, the final score of the stored energy can be obtained only by multiplying and summing the numerical value after one type of stored energy index normalization and the corresponding index. The score is in direct proportion to the scene fitness, the total score of all types of energy storage is compared, and the score is higher to indicate that the score is more suitable for the current scene.
Claims (8)
1. A method for evaluating quantitative energy storage under multiple scenes is characterized by comprising the following steps:
(1) and establishing an evaluation index of the stored energy.
(2) The scores were normalized using the z-score normalization method.
(3) And selecting the weight by adopting a matrix judgment method according to different scenes.
(4) And obtaining the energy storage score condition under the current scene.
2. The method for quantitatively evaluating the stored energy under the multiple scenes according to claim 1, wherein the step (1) comprises the following steps:
(a) and selecting evaluation indexes, wherein the selected indexes are divided into four categories, namely economic indexes, technical performance indexes, environmental impact indexes and indexes related to a power grid. The economic indexes comprise daily cost of energy storage, real-time electric quantity benefit of the energy storage and daily standby power benefit; the technical performance indexes comprise energy storage life and cycle times; the environmental impact indexes comprise unit capacity carbon dioxide emission and unit capacity land occupation area; the indexes related to the power grid comprise the indexes of delaying the upgrading benefit of the power grid, equivalent load standard deviation and reliability.
(b) And obtaining evaluation index data. The energy storage service life, the carbon dioxide emission amount per unit volume and the land occupation area per unit volume are obtained through basic data provided by an energy storage factory, and calculation is not needed. The rest indexes need to be obtained through calculation.
3. The method for quantitatively evaluating stored energy under multiple scenes according to claim 2, wherein the index obtained by calculation in step (b) comprises:
(1) calculation of economic indicators
The daily cost calculation method for energy storage comprises the following steps:
in the formula: cpUnit power cost for stored energy; cECost per capacity for stored energy; prRated power for stored energy; erRated capacity for stored energy; d is the energy storage life; r is the discount rate; cfDaily operation and maintenance cost of unit energy for energy storage; ps is a force output value at each moment of energy storage, and according to a power supply convention, Ps is positive during energy storage discharge and is negative during charging; t is the total scheduling time number; Δ t is the scheduling time interval.
The real-time electric quantity benefit of the stored energy is that the stored energy is charged when the electricity price is low, the stored energy is discharged when the electricity price is high, the obtained price difference profit is obtained, and the calculation formula is as follows:
in the formula: celcThe electricity prices at each time.
The reserve power of energy storage refers to the up-down adjustable allowance of the energy storage power between the maximum and minimum charge-discharge power, and the reserve power can be used as the reserve power of a power grid, and the obtained benefit is the reserve power benefit of the energy storage. The term "up-regulation" means that the discharge amount of stored energy increases or the charge amount decreases, and the term "down-regulation" means that the discharge amount of stored energy increases or the charge amount decreases. The formula for the daily reserve power gain is then:
in the formula: a. theuFor up-regulation of the subsidy price, AdFor lowering the subsidy price.
(2) Calculation of technical performance indicators
The number of cycles of energy storage is related to the depth of discharge, the higher the depth of charge and discharge, the fewer the number of cycles of the battery. And adopting 0.2C multiplying power, and obtaining a calculation formula of the cycle number of the battery by fitting, wherein the calculation formula is as follows:
N0.2c＝3946×(Dod)-1.58 (6)
in the formula: dod is the Depth of discharge (Depth of discharge) of the stored energy.
(3) Grid-related index calculation
The calculation formula of the equivalent load standard deviation is as follows:
Pnetload＝Plood-Pnew (8)
in the formula: pnetloadIs the net load power, P, of the systemloadFor load power, PnewFor new energy output power value, PavIs the average of the payload power.
The calculation formula for delaying the upgrading benefit of the power grid is as follows:
in the formula: ctransThe unit replacement cost for the transformer; pmaxThe maximum value of the load power; tau is the annual load growth rate; Δ M is the postponable upgrading and capacity expanding life of the power grid, and λ is the peak clipping rate of stored energy; clineThe unit cost for line capacity expansion.
4. The method for quantitative energy storage evaluation under multiple scenes as claimed in claim 1, wherein in the step (2), the z-score normalized calculation formula is:
in the formula: x is the number ofiIs the original value of the i-th index, yiThe number of the ith index after the normalization processing is shown, n is the number of objects to be compared and corresponds to the number of the energy storage types to be compared, and s is the standard deviation. y isiThe first expression of (a) is a revenue-type metric and the second expression is a cost-type metric. After z-score normalization, 0 represents the mean level, greater than 0 represents greater than the mean level, less than 0 represents less than the mean level, and larger absolute values represent greater or lesser than the mean level.
5. The method for quantitatively evaluating the energy storage under the multiple scenes according to claim 1, wherein the step (3) is specifically as follows:
the idea of judging the matrix is to compare the indexes two by two. When n indexes exist, the corresponding judgment matrix is as follows:
after the judgment matrix is filled, the characteristic values of the judgment matrix are calculated, the maximum characteristic value is found, the characteristic vector corresponding to the judgment matrix is calculated, and the corresponding weight relation among the n indexes can be obtained by unitization.
Defining the consistency index CI of the judgment matrix as follows:
in the formula: lambda [ alpha ]maxThe maximum eigenvalue of the judgment matrix is shown, and n is the number of indexes compared. And when the I is less than or equal to 0.1, the judgment matrix is considered to pass the consistency check, otherwise, the judgment matrix is refilled.
6. The method for quantitatively evaluating the energy storage under the multiple scenes according to claim 1, wherein the step (4) is specifically as follows:
and multiplying and summing the normalized numerical value of the energy storage index and the corresponding index to obtain the final score of the energy storage. And comparing the final total scores of all types of energy storage, wherein the higher score represents the more suitable score for the current scene.
7. The method for quantitatively evaluating the stored energy under the multiple scenes as claimed in claim 2, wherein the reliability index is the expected value of the system power shortage in one day calculated by adopting monte carlo simulation after the failure rate of the given device is given.
8. The method for quantitatively evaluating the stored energy under the multiple scenes as claimed in claim 3, wherein the new energy output power value PnewIncluding photovoltaic output values, fan output values, and the like.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114819424A (en) * | 2022-06-30 | 2022-07-29 | 国网江西省电力有限公司电力科学研究院 | Energy storage residual capacity distribution method suitable for multi-scene application |
| CN116108357A (en) * | 2023-04-11 | 2023-05-12 | 武汉大学 | Electrolytic aluminum FCM clustering method and system considering adjustment capability difference |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106548413A (en) * | 2016-10-18 | 2017-03-29 | 中国电力科学研究院 | A kind of power system energy storage fitness-for-service assessment method and system |
| CN112001598A (en) * | 2020-07-28 | 2020-11-27 | 四川大学 | Energy storage configuration evaluation and operation optimization method for different users based on energy storage type selection |
| CN112434446A (en) * | 2020-12-14 | 2021-03-02 | 海南电网有限责任公司 | Distributed energy storage economy evaluation method based on full life cycle |
| CN112907129A (en) * | 2021-03-24 | 2021-06-04 | 国网安徽省电力有限公司蚌埠供电公司 | Energy storage comprehensive benefit evaluation index system |
-
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106548413A (en) * | 2016-10-18 | 2017-03-29 | 中国电力科学研究院 | A kind of power system energy storage fitness-for-service assessment method and system |
| CN112001598A (en) * | 2020-07-28 | 2020-11-27 | 四川大学 | Energy storage configuration evaluation and operation optimization method for different users based on energy storage type selection |
| CN112434446A (en) * | 2020-12-14 | 2021-03-02 | 海南电网有限责任公司 | Distributed energy storage economy evaluation method based on full life cycle |
| CN112907129A (en) * | 2021-03-24 | 2021-06-04 | 国网安徽省电力有限公司蚌埠供电公司 | Energy storage comprehensive benefit evaluation index system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114819424A (en) * | 2022-06-30 | 2022-07-29 | 国网江西省电力有限公司电力科学研究院 | Energy storage residual capacity distribution method suitable for multi-scene application |
| CN114819424B (en) * | 2022-06-30 | 2022-10-11 | 国网江西省电力有限公司电力科学研究院 | Energy storage residual capacity distribution method suitable for multi-scene application |
| CN116108357A (en) * | 2023-04-11 | 2023-05-12 | 武汉大学 | Electrolytic aluminum FCM clustering method and system considering adjustment capability difference |
| CN116108357B (en) * | 2023-04-11 | 2023-08-15 | 武汉大学 | Electrolytic aluminum FCM clustering method and system considering adjustment capability difference |
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