Optimal selection method of energy storage technical scheme

Abstract

The invention discloses an optimal selection method of an energy storage technical scheme. The method comprises the following steps: S1, establishing a decision framework of the energy storage technical scheme; s2, adding the virtual alternative scheme into a decision framework to obtain an anti-reverse-order framework; s3, optimizing the energy storage technical schemes according to the net flow indexes of the technical schemes in the anti-reverse-order framework, and according to the method, the anti-reverse-order framework is used for reducing the influence of the reverse-order problem on energy storage technology selection when the PROMETHEE method is used, so that the most preferential energy storage technical scheme is obtained.

Description

Technical Field

[0001] The present application relates to the field of energy storage technology, and in particular to a method for optimizing an energy storage technology solution. Background Art

[0002] Renewable energy sources such as solar and wind power are intermittent and unstable. Energy storage technology can be used to store excess electricity and release it during peak demand periods, balancing the time difference between power generation and power consumption and reducing energy losses caused by supply and demand mismatch. Due to the above advantages, energy storage technology has been widely used in peak load regulation, frequency regulation, grid backup power supply and renewable energy consumption. Since the application scenarios of energy storage technology are complex and diverse, appropriate energy technology should be selected for different application scenarios. Given that multiple criteria need to be considered when selecting energy storage technology, the energy storage technology selection problem can be viewed as a multi-criteria decision-making problem.

[0003] In existing studies, the PROMETHEE method has been used to solve this multi-criteria decision-making problem, but the PROMETHEE method has an inverse phenomenon, and the addition and deletion of alternatives may lead to changes in the optimal alternative. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for optimizing an energy storage technology solution to solve the inverse order problem that may occur in the PROMETHEE method when selecting energy storage technology.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a preferred method of an energy storage technical solution, comprising: S1. Build a decision-making framework for energy storage technology solutions; S2, adding virtual alternatives into the decision framework to obtain an anti-reversal framework; S3. Optimize the energy storage technology solutions based on the net flow index of the technical solutions in the anti-reversal framework.

[0006] Further: The original evaluation value matrix corresponding to the decision framework of the energy storage technology solution M The expression is:

[0007] in, Represents an alternative energy storage technology In Properties The following evaluation, for n Energy storage technology alternatives consisting of a set of alternatives A The elements in are represented as , for mThe attribute set consists of C The elements in are represented as .

[0008] Further: S2 includes: S21. Calculate the equally spaced virtual evaluation value under each attribute according to the number of virtual alternatives; S22, the same position m The equally spaced virtual evaluation values ​​are used as a virtual equally spaced alternative; S23. Add virtual equally spaced alternatives of the same number of virtual alternatives into the decision framework to obtain an anti-reversal framework.

[0009] Further: For the evaluation value vector , the equally spaced virtual evaluation values ​​under each attribute The calculation formula is:

[0010] in, q is the number of virtual alternatives, p The virtual evaluation value used in the attribute The next position, Counting mark.

[0011] Further: Anti-reversal framework , and its corresponding evaluation value matrix It is expressed as:

[0012] in, express m Equally spaced virtual evaluation values ( ) constitutes a virtual equidistant alternative.

[0013] Further: S3 includes: S31. Calculate any two alternatives in the anti-reversal framework and The overall preference strength under any attribute ; S32. Based on the comprehensive preference intensity Calculation method to determine alternative solutions Net flow indicator; S33, repeating S31-S33 until the net flow index of each alternative solution in the anti-reversal framework is calculated; S34. Sort the alternatives according to the net flow index, and select the alternative with the highest net flow index as the preferred energy storage technology solution.

[0014] Further: Comprehensive preference strength The calculation expression is:

[0015] in, Indicates alternatives Compared to alternatives In Properties The strength of preference.

[0016] Further: Alternatives Net flow indicator The expression is:

[0017] in, As an alternative The net outflow indicator, As an alternative The net inflow indicator.

[0018] The beneficial effects of the present invention are: The present invention reduces the inherent reverse order phenomenon of the PROMETHEE method by building an anti-reverse order framework, thereby avoiding the impact of the reverse order problem on energy storage decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 The present invention is a flow chart of the optimization method for energy storage technology solutions. DETAILED DESCRIPTION

[0020] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0021] like Figure 1 As shown, in one embodiment of the present invention, a preferred method of an energy storage technical solution is provided, comprising: S1. Build a decision-making framework for energy storage technology solutions; S2, adding virtual alternatives into the decision framework to obtain an anti-reversal framework; S3. Optimize the energy storage technology solutions based on the net flow index of the technical solutions in the anti-reversal framework.

[0022] Specifically, in this embodiment, the PROMETHEE method is used to consider the following decision problem: a decision maker needs ton Alternative options (i.e. n Select the best alternative from the alternative energy storage technologies. n Alternative solutions form an alternative solution set, which is expressed as , the decision maker has a choice for each alternative m Evaluate under each attribute. m attributes form an attribute set, expressed as .

[0023] The original evaluation value matrix corresponding to the decision framework of energy storage technology solutions M The expression is:

[0024] in, Represents an alternative energy storage technology In Properties The following evaluation, for n Energy storage technology alternatives consisting of a set of alternatives A The elements in for m The attribute set consists of C The elements in .

[0025] Before building the anti-reversal framework, it is necessary to determine the number of virtual alternatives, that is, the level of the anti-reversal framework, expressed as q , level q is a positive integer greater than 1.

[0026] Specifically, S2 includes: S21. Calculate the equally spaced virtual evaluation value under each attribute according to the number of virtual alternatives; S22, the same position m The equally spaced virtual evaluation values ​​are used as a virtual equally spaced alternative; S23. Add virtual equally spaced alternatives of the same number of virtual alternatives into the decision framework to obtain an anti-reversal framework.

[0027] In S21, for the evaluation value vector , the equally spaced virtual evaluation values ​​under each attribute The calculation formula is:

[0028] in, q is the number of virtual alternatives, p The virtual evaluation value used in the attribute The next position, is the counting mark. According to the above formula, as p As the value of is increased, the virtual evaluation value of equal spacing will also increase.

[0029] In S22, for the same p Value, yes m Equally spaced virtual evaluation values ( );this m The evaluation value can be regarded as a virtual alternative Since the distance between the evaluation values ​​of any two virtual alternatives is equal under each attribute, Also known as the virtual equidistant alternative. , so the number of virtual equally spaced alternatives is q。

[0030] In S23, the anti-reversal framework , and its corresponding evaluation value matrix It is expressed as:

[0031] in, express m Equally spaced virtual evaluation values ( ) constitutes a virtual equidistant alternative.

[0032] Specifically, S3 includes: S31. Calculate any two alternatives in the anti-reversal framework and The overall preference strength under any attribute ; S32. Based on the comprehensive preference intensity Calculation method to determine alternative solutions Net flow indicator; S33, repeating S31-S33 until the net flow index of each alternative solution in the anti-reversal framework is calculated; S34. Sort the alternatives according to the net flow index, and select the alternative with the highest net flow index as the preferred energy storage technology solution.

[0033] In S31, the overall preference intensity The calculation expression is:

[0034] in, Indicates alternatives Compared to alternatives In Properties The strength of preference under S32, alternative Net flow indicator The expression is:

[0035] in, As an alternative The net outflow indicator, As an alternative The net inflow indicator.

[0036] In one embodiment of the present invention, the effectiveness of the proposed anti-reversal framework in reducing the probability of reversal is evaluated through Monte Carlo simulation analysis. First, three simulation parameters are considered: the number of alternatives, the number of attributes, and the number of layers of the anti-reversal framework. In this simulation experiment, the number of alternatives is set to 3, 6, 9, 12, 15; the number of attributes is set to 3, 6, 9, 12, 15; the number of layers of the anti-reversal framework is set to 3, 5, 7, 9, 11, 13, 15, 17. It is easy to see that the values ​​of the three simulation parameters have a total of There are 200 combinations corresponding to 200 decision-making situations.

[0037] For each decision-making scenario, the probability of reverse order of the PROMETHEE method when the anti-reversal framework is not used and the probability of reverse order of the PROMETHEE method when the anti-reversal framework is used are calculated through simulation analysis. The results show that in all decision-making scenarios, the probability of reverse order of the PROMETHEE method when the anti-reversal framework is not used is higher than the probability of reverse order of the PROMETHEE method when the anti-reversal framework is used. Specifically, the probability of reverse order of the PROMETHEE method when the anti-reversal framework is not used is about 0.4 on average, and the probability of reverse order after using the anti-reversal framework is reduced by about 0.1964 on average, a reduction of 49.1%. The above simulation results show that the use of the anti-reversal framework can reduce the probability of reverse order of the PROMETHEE method.

[0038] In one embodiment of the present invention, standardized evaluation values ​​of 11 energy storage technologies under 15 attributes are collected and shown in Table 1.

[0039] Table 11 Standardized evaluation values ​​of 11 energy storage technologies under 15 attributes

[0040] Using the optimization method of the energy storage technology solution provided in this application, the ranking of the alternative solutions is as follows:

[0041] According to the sorting, you should choose to use Sodium sulfur battery. During the project construction phase, a new energy storage technology emerged, and its evaluation values ​​under 15 attributes were 0.71, 0.18, 0.11, 0.16, 0.16, 0.52, 0.85, 0.92, 0.23, 0.46, 0.1, 0.89, 0.57, 0.77, 0.31. The 11 technologies in Table 1 of the new technology connection were brought into the PROMETHEE method with a stress-resistant framework for analysis, and the ranking of the original 11 alternative energy storage technologies was obtained as follows:

[0042] In this case, adding new energy storage technology does not change The decision that sodium-sulfur batteries are the optimal technology.

[0043] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing an energy storage technology solution, characterized in that: include: S1. Build a decision-making framework for energy storage technology solutions; S2, adding virtual alternatives into the decision framework to obtain an anti-reversal framework; S3. Optimize the energy storage technology solutions based on the net flow index of the technical solutions in the anti-reversal framework.

2. The optimization method of the energy storage technology solution according to claim 1 is characterized in that: In S1, the original evaluation value matrix corresponding to the decision framework of the energy storage technology solution M The expression is: in, Represents an alternative energy storage technology In Properties The following evaluation, for n Energy storage technology alternatives consisting of a set of alternatives A The elements in are represented by , for m The attribute set consists of C The elements in are represented by .

3. The optimization method of the energy storage technology solution according to claim 2, characterized in that S2 include: S21. Calculate the equally spaced virtual evaluation value under each attribute according to the number of virtual alternatives; S22, the same position m The equally spaced virtual evaluation values ​​are used as a virtual equally spaced alternative; S23. Add virtual equally spaced alternatives of the same number of virtual alternatives into the decision framework to obtain an anti-reversal framework.

4. The optimization method of the energy storage technology solution according to claim 3 is characterized in that: In S21, for the evaluation value vector , the equally spaced virtual evaluation values ​​under each attribute The calculation formula is: in, q is the number of virtual alternatives, p The virtual evaluation value used in the attribute The next position, Counting mark.

5. The optimization method of the energy storage technology solution according to claim 3 is characterized in that: In S23, the anti-reversal framework , and its corresponding evaluation value matrix It is expressed as: in, express m Equally spaced virtual evaluation values ( ) constitutes a virtual equidistant alternative.

6. The method for optimizing the energy storage technology solution according to claim 1, characterized in that S3 include: S31. Calculate any two alternatives in the anti-reversal framework and The overall preference strength under any attribute ; S32. Based on the comprehensive preference intensity Calculation method to determine alternative solutions Net flow indicator; S33, repeating S31-S33 until the net flow index of each alternative solution in the anti-reversal framework is calculated; S34. Sort the alternatives according to the net flow index, and select the alternative with the highest net flow index as the preferred energy storage technology solution.

7. The optimization method of the energy storage technology solution according to claim 6 is characterized in that: In S31, the overall preference intensity The calculation expression is: in, Indicates alternatives Compared to alternatives In Properties The strength of preference.

8. The optimization method of the energy storage technology solution according to claim 6 is characterized in that: S32, alternative Net flow indicator The expression is: in, As an alternative The net outflow indicator, As an alternative The net inflow indicator.

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