Multi-element energy storage evaluation method and evaluation system adaptive to novel power system

Abstract

The invention provides a multivariate energy storage evaluation method and evaluation system adaptive to a novel power system. The method comprises the steps of obtaining an evaluation dimension set, a quantitative index set and an initial weight value according to an application scene; obtaining a quantitative index value set based on the quantitative index set; obtaining a first weight value set and a second weight value set according to the initial weight value and a weight adjustment mechanism, wherein the first weight value set and the second weight value set are the weight of the evaluation dimension and the weight of the quantitative index respectively; obtaining a target layer score according to the quantitative index value set, the first weight value set and the second weight value set; and obtaining an investment decision according to the target layer score. The multivariate energy storage evaluation method adaptive to the novel power system is diversified in evaluation dimension and adopts non-uniform dynamic weights, can reduce prejudice risks and decision risks, is high in environmental adaptability, prevents the existing evaluation result from being disjointed with actual landing demands, and ensures that the evaluation result fits an actual investment environment for a long time.

Description

Technical Field

[0001] This invention relates to the field of evaluation technology for energy storage technologies in new power systems, and specifically to a multi-element energy storage evaluation method and system adapted to new power systems. Background Technology

[0002] With the advancement of the "dual carbon" goals, the application scale of diversified energy storage (such as pumped hydro storage, lithium battery energy storage, and vanadium redox flow battery energy storage) in new power systems is rapidly expanding. New energy storage is an important technology and basic equipment for building new power systems. To realize new energy storage, it is necessary to promote energy storage applications in different scenarios, strengthen the synergistic optimization of energy storage with new energy sources and the power grid, establish and improve new energy storage technology standards and evaluation systems, and support the achievement of carbon peaking goals in the energy sector.

[0003] The current evaluation of energy storage faces the following key issues: (1) Single evaluation dimension: The evaluation methods or assessment systems in the existing technologies mostly focus on the performance of energy storage technologies, resulting in incomplete information, failure to reflect complexity and diversity, poor environmental adaptability, and easy to lead to bias risk and decision risk; (2) Insufficient scenario adaptability: The use of the existing evaluation system with uniform indicator weights cannot promote the optimization of energy storage according to different scenarios; (3) Poor quantification and practicality: Most evaluation indicators lack clear calculation methods and data sources; (4) Lack of regional specificity: When evaluating power systems with unique power supply structures and load characteristics, the evaluation results may be out of touch with actual implementation needs. Summary of the Invention

[0004] This invention addresses the problems existing in the prior art by providing a multi-dimensional energy storage evaluation method adapted to new power systems, which has diverse evaluation dimensions and adopts non-uniform dynamic weights. This method can reduce bias risk and decision risk, has strong environmental adaptability, avoids the disconnect between current evaluation results and actual implementation needs, and ensures that the evaluation results are consistent with the actual investment environment in the long term.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention proposes a multi-element energy storage evaluation method adapted to new power systems, comprising: acquiring application scenarios and weight adjustment mechanisms; acquiring an evaluation dimension set, a quantitative index set, and initial weight values ​​based on the application scenarios, wherein the evaluation dimension set is a set of evaluation dimensions and the quantitative index set is a set of quantitative indicators; and acquiring a quantitative index value set based on the quantitative index set, wherein the quantitative index value set is a set of numerical values ​​of quantitative index values. A first weight value set and a second weight value set are obtained based on the initial weight values ​​and the weight adjustment mechanism. The first weight value set is the set of values ​​for the first weight, which is the weight of the evaluation dimension. The second weight value set is the set of values ​​for the second weight, which is the weight of the quantitative indicator. A target layer score is obtained based on the quantitative indicator value set, the first weight value set, and the second weight value set. An investment decision is obtained based on the target layer score.

[0006] In some embodiments, obtaining the target layer score based on the set of quantified index values, the first set of weight values, and the second set of weight values ​​includes: Obtain the set of full scores for quantitative indicators, wherein the set of full scores for quantitative indicators is a set of numbers containing the full scores of quantitative indicators; A standardized score set is obtained based on the full score of the indicator and the set of quantitative indicator values; The criterion layer score set is obtained based on the standardized score set and the second weight set; The target layer score is obtained based on the score set of the evaluation dimensions and the first weight set.

[0007] In some embodiments, the evaluation dimensions are technical reliability, economic profitability, environmental compliance, or market and scenario adaptability.

[0008] In some embodiments, when the evaluation dimension is the technical reliability, the set of quantitative indicators includes a performance assurance indicator group and a risk control indicator group.

[0009] In some embodiments, when the evaluation dimension is economic profitability, the set of quantitative indicators includes a cost control indicator group and a profitability indicator group.

[0010] In some embodiments, when the evaluation dimension is environmental compliance, the set of quantitative indicators includes a carbon cost indicator group and a compliance risk indicator group.

[0011] In some embodiments, when the evaluation dimension is the market and scenario adaptability, the quantitative indicator set includes a market return indicator group and a policy dividend indicator group.

[0012] In some embodiments, obtaining the first weight value set and the second weight value set based on the initial weight values ​​and the weight adjustment mechanism includes: The system acquires preset adjustment cycles, local impact changes, and substantial impact changes; the local impact changes include any of the following: changes in power supply structure, load characteristic adjustments, or updates to regional energy storage policies. The substantial impactful changes include any one of the following: updates to evaluation dimensions, updates to indicator groups, or updates to quantitative indicators; Based on the weight adjustment conditions, and according to the preset adjustment period, local impact changes, and substantial impact changes, the initial weight values ​​are adjusted to obtain the first weight value set and the second weight value set.

[0013] In some embodiments, when the target layer score is At that time, the investment decision is a priority investment; When the target layer score is At that time, the investment decision was a prudent investment; When the target layer score is At that time, the investment decision was to restrict investment; When the target layer score is At that time, the investment decision was a negative investment; in, To score the target layer, The first threshold, The second threshold, This is the third threshold.

[0014] Secondly, this invention proposes a multi-element energy storage evaluation system adapted to new power systems, which is constructed using the multi-element energy storage evaluation method adapted to new power systems, including a data acquisition unit, a weight adjustment unit, a calculation unit, and a decision-making unit. The data acquisition unit is used to acquire application scenarios and weight adjustment mechanisms, to acquire evaluation dimension sets, quantitative indicator sets and initial weight values ​​according to the application scenarios, and to acquire quantitative indicator value sets based on the quantitative indicator sets. The weight adjustment unit is used to obtain a first weight value set and a second weight value set according to the initial weight values ​​and the weight adjustment mechanism; The calculation unit is used to obtain the target layer score based on the set of quantitative index values, the first set of weight values, and the second set of weight values. The decision-making unit is used to obtain investment decisions based on the target layer score.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention utilizes multiple evaluation dimensions based on application scenarios, providing complete and diverse information, thereby reducing bias and decision-making risks. It is highly adaptable to different environments and avoids the disconnect between current evaluation results and actual implementation needs. It employs non-uniform weights and adjusts them according to a weight adjustment mechanism to ensure that the evaluation results remain consistent with the actual investment environment in the long term. 2. This invention relates to ensuring the accuracy of raw data through cross-departmental verification, guaranteeing the reliability of investment calculation data, and all data sources are channels that enterprises can directly access, without relying on additional data provided by government departments. Furthermore, the quantitative indicators are unambiguous and can be directly substituted into calculations, supporting rapid project screening and decision-making. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the multi-element energy storage evaluation method adapted to a novel power system in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a multi-element energy storage evaluation system adapted to a novel power system in an embodiment of the present invention. Figure I ; Figure 3 This is a schematic diagram of the structure of a multi-element energy storage evaluation system adapted to a novel power system in an embodiment of the present invention. Figure II . Detailed Implementation

[0017] The core objective of comprehensive evaluation of multi-dimensional energy storage is to comprehensively assess the feasibility of energy storage projects from multiple dimensions, including technology, economy, environment, and operation. However, existing evaluation methods or assessment systems often focus only on the performance of energy storage technology, neglecting the coordinated evaluation of economic rationality and environmental friendliness. Furthermore, existing assessment systems fail to consider the differences in core needs of energy storage on the power generation side, grid side, and user side, using uniform indicator weights, which cannot promote scenario-specific optimization of energy storage. Most evaluation indicators lack clear calculation methods and data sources, and no dynamic optimization mechanism has been established. When evaluating power systems with unique power structure and load characteristics, such as provincial power systems, the evaluation does not take into account the characteristics of the province, resulting in a disconnect between evaluation results and actual implementation needs. Therefore, there is an urgent need for a multi-dimensional, scenario-based, and quantifiable multi-dimensional energy storage evaluation indicator system to address the adaptability and practicality deficiencies of existing technologies.

[0018] To clearly illustrate the technical features of this solution, the implementation methods of this application will be described in detail below with reference to the accompanying drawings and embodiments. This will allow for a full understanding and implementation of how this application uses technical means to solve technical problems and achieve corresponding technical effects. The embodiments of this application and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this application.

[0019] See Figure 1 In the first aspect, embodiments of the present invention propose a multi-element energy storage evaluation method adapted to new power systems, including: obtaining application scenarios and weight adjustment mechanisms; the application scenarios of multi-element energy storage typically include the power source side, the grid side, and the user side, and the application scenarios of the project to be evaluated are specified by the enterprise's investment management department; Based on the application scenario, obtain the evaluation dimension set, quantitative indicator set, and initial weight values. The evaluation dimension set is a collection of evaluation dimensions, and the quantitative indicator set is a collection of quantitative indicators. Retrieve the criterion layer and indicator layer corresponding to the application scenario. The criterion layer serves as the evaluation dimension set, and the indicator layer serves as the quantitative indicator set. The initial weight values ​​serve as the evaluation basis and are set using the Analytic Hierarchy Process (AHP), including the weight values ​​of each evaluation dimension in the criterion layer and the weight values ​​of each indicator group in each evaluation dimension. The quantitative indicator value set is obtained based on the quantitative indicator set, which is a numerical set of quantitative indicator values. Equipment parameters, economic, environmental compliance, market and operation data related to the evaluation dimensions are collected and classified. After removing outliers, they are used as quantitative indicator values. Cross-departmental verification is used to ensure data accuracy and the reliability of investment calculation data. All data sources are channels that enterprises can directly access, without relying on additional data provided by government departments. The first weight value set and the second weight value set are obtained based on the initial weight values ​​and the weight adjustment mechanism. The first weight value set is the set of values ​​for the first weight, which is the weight of the evaluation dimension. The second weight value set is the set of values ​​for the second weight, which is the weight of the quantitative indicator. The target layer score is obtained based on the set of quantitative indicator values, the first weight value set, and the second weight value set; investment decisions are made based on the target layer score.

[0020] The advantages are that this invention calls upon multiple evaluation dimensions based on application scenarios, providing complete and diverse information, thereby reducing the risk of bias and decision-making, and has strong environmental adaptability, avoiding the disconnect between current evaluation results and actual implementation needs; it adopts non-uniform weights and adjusts them according to a weight adjustment mechanism to ensure that the evaluation results are consistent with the actual investment environment in the long term. In some embodiments, the evaluation dimensions are technical reliability, economic profitability, environmental compliance, or market and scenario adaptability.

[0021] The indicator groups include, but are not limited to, the performance assurance indicator group, the risk control indicator group, the cost control indicator group, the profitability indicator group, the carbon cost indicator group, the compliance risk indicator group, the market return indicator group, and the policy dividend indicator group. In some embodiments, when the evaluation dimension is technical reliability, the quantitative indicator set includes a performance assurance indicator group and a risk control indicator group; wherein, the performance assurance indicator group includes quantitative indicators such as the energy density of the energy storage project, the cycle efficiency of the energy storage project, the response speed of the energy storage project, and the number of charge and discharge cycles of the energy storage project; the risk control indicator group includes quantitative indicators such as annual availability, fault recovery time, and fault loss cost.

[0022] When the evaluation dimension is technical reliability, the values ​​of the quantitative indicators are derived from equipment parameter data or calculated based on equipment parameter data. The equipment parameter data comes from the factory parameters such as energy density and cycle efficiency provided by the energy storage equipment manufacturer. In some embodiments, when the evaluation dimension is economic profitability, the quantitative indicator set includes a cost control indicator group and a profitability indicator group; wherein, the cost control indicator group includes quantitative indicators such as levelized cost of electricity (LCOE), unit construction investment and annual operation and maintenance cost coefficient; the profitability indicator group includes quantitative indicators such as investment payback period, net revenue per kilowatt-hour, and annual return on assets (ROA).

[0023] When the evaluation dimension is economic profitability, the values ​​of quantitative indicators are derived from economic data or calculated based on economic data. The economic data comes from the levelized cost of electricity (LCOE) calculated by the enterprise, unit construction investment, annual operation and maintenance cost coefficient, peak-valley price difference published by the electricity market trading platform, and ancillary service transaction price data, etc. In some embodiments, when the evaluation dimension is environmental compliance, the quantitative indicator set includes a carbon cost indicator group and a compliance risk indicator group; wherein, the carbon cost indicator group includes quantitative indicators such as total life cycle carbon emissions and unit carbon emission costs; the compliance risk indicator group includes quantitative indicators such as resource recycling rate, noise pollution, and resource recycling and disposal costs.

[0024] When the evaluation dimension is environmental compliance, the values ​​of the quantitative indicators are derived from environmental compliance data or calculated based on environmental compliance data. Environmental compliance data comes from the unit carbon emission cost data updated in real time by the carbon trading platform, the resource recycling rate and disposal cost quotation provided by energy storage equipment recycling companies, and noise monitoring reports issued by third-party environmental testing agencies, etc. In some embodiments, when the evaluation dimension is market and scenario adaptability, the quantitative indicator set includes a market revenue indicator group and a policy dividend indicator group; wherein, the market revenue indicator group includes quantitative indicators such as the adaptability of new energy consumption, load matching degree, the proportion of ancillary service market revenue and spot market arbitrage space; the policy dividend indicator group includes quantitative indicators such as multi-market participation capability, the amount of policy subsidies obtained and the strength of land / tax incentives.

[0025] When the evaluation dimension is market and scenario adaptability, the values ​​of the quantitative indicators are derived from market and operational data or calculated based on market and operational data. Market and operational data come from transaction records of energy storage projects participating in the spot / ancillary service market recorded by the enterprise's operations department, policy subsidies issued by local energy bureaus, and land / tax incentive documents, etc.

[0026] Preferably, the weight of "economic profitability" is increased, including financial indicators such as annual return on assets (ROA) and annual operation and maintenance cost coefficient, which are directly related to the calculation of corporate investment returns and help companies quickly identify projects with high profit potential; hidden risks such as technical failures and environmental penalties are transformed into quantifiable cost data, which can help companies avoid investment risks in advance, and the indicators have no ambiguous descriptions and can be directly substituted into the calculation, supporting rapid project screening and decision-making. In this embodiment, the initial weight values ​​are shown in Table 1: Table 1 Initial Weight Values The total weight of the quantitative indicators in each indicator group is equal to the weight of that indicator group, and the total weight of the indicator group in each evaluation dimension is equal to the weight of that evaluation dimension. In some embodiments, obtaining the first weight value set and the second weight value set based on the initial weight values ​​and the weight adjustment mechanism includes: Acquire preset adjustment cycles, local impact changes, and substantial impact changes; local impact changes include any change in power supply structure, load characteristic adjustment, or regional energy storage policy update; Substantial changes include any one of the following: updates to evaluation dimensions, updates to indicator groups, or updates to quantitative indicators; Based on the weight adjustment conditions, the initial weight values ​​are adjusted according to the preset adjustment period, local impact changes, and substantial impact changes to obtain the first weight value set and the second weight value set.

[0027] The weight adjustment conditions include a first condition, a second condition, and a third condition. When any one of the first, second, or third conditions is met, the initial weight values ​​are adjusted to obtain a first weight value set and a second weight value set. In addition, the adjusted first and second weight value sets replace the original initial weight values ​​and are updated to new initial weight values. The first condition is that the preset adjustment period is reached. Typically, the preset adjustment period is 2 years, which enables the regular adjustment of the weight values. When the first condition is met, based on the electricity market price level and the progress of energy storage technology, the weight values ​​of all or some weight values ​​in the target layer are adjusted by expert scoring method to adapt to the dynamic factors that enterprises care about, such as electricity market price fluctuations and energy storage technology iterations, so as to ensure that the evaluation results are consistent with the actual investment environment in the long term. The second condition is that when a local impact occurs at the project implementation site, the local impact includes any change in the power supply structure, load characteristics adjustment or regional energy storage policy update. When the second condition is met, the weight values ​​of the evaluation dimension associated with the local impact change and the weight values ​​of the indicator group in that evaluation dimension in the criterion layer are adjusted. The third condition is when a substantial change occurs. Substantial changes include any of the following: updates to evaluation dimensions, indicator groups, or quantitative indicators. These changes are usually determined by updates to national policies. Updates to evaluation dimensions include adding or removing evaluation dimensions. Updates to indicator groups include adding or removing indicator groups. Updates to quantitative indicators include adding or removing quantitative indicators. For example, adding environmental evaluation dimensions based on policies, or setting new evaluation dimensions, indicator groups, or quantitative indicators in different project implementation locations based on different evaluation requirements. When the third condition is met: adjust all weight values ​​within the target layer; If a new evaluation dimension is added, the indicator groups and quantitative indicators in the new evaluation dimension will be supplemented or adjusted within a preset time period. After the supplementation or adjustment, all weight values ​​in the target layer will be adjusted. If evaluation dimensions are reduced, the indicator groups and quantitative indicators in the reduced evaluation dimensions will be reduced or adjusted within a preset time period. After the reduction or adjustment, all weight values ​​in the target layer will be adjusted. If a new indicator group is added, the criteria layer allocation of the new indicator group and the supplementation or adjustment of the quantitative indicators in the indicator group will be carried out within the preset time period. After allocation and supplementation or adjustment, all weight values ​​in the target layer will be adjusted. If an indicator group is deleted, the quantitative indicators in the deleted indicator group will be deleted or adjusted within a preset time period. After deletion or adjustment, all weight values ​​in the target layer will be adjusted. If a new quantitative indicator is added, the indicator group for the new quantitative indicator will be allocated within a preset time period, and all weight values ​​in the target layer will be adjusted after allocation. If quantitative indicators are removed, all weight values ​​within the target layer will be adjusted within a preset time period. The preset duration is usually 3 months.

[0028] In some embodiments, obtaining the target layer score based on a set of quantized index values, a first set of weight values, and a second set of weight values ​​includes: Obtain the set of full scores for quantitative indicators. The set of full scores for quantitative indicators is a set of numbers containing the full scores of quantitative indicators. A standardized score set is obtained based on the full score of the indicator and the set of quantitative indicator values; The standardized score set is the set of standardized scores for each quantitative indicator; quantitative indicators include positive and negative indicators, meaning the standardized scores include standardized scores for both positive and negative indicators. ; ; in, For the first The first criterion level The standardized score of the positive indicators of each quantitative metric. For the first The first criterion level The negative standardized score of each quantitative indicator. This refers to the criterion level number, i.e., the evaluation dimension number. This refers to the index of the quantitative indicator under the corresponding criterion level. For the first The first criterion level The value of a quantitative indicator, This represents the minimum acceptable value for the quantitative indicator. The optimal value for the quantitative indicator. For the first The first criterion level The full score of each quantitative indicator; To simplify calculations: When the quantitative indicator is a positive indicator, the standardized score set contains the standardized scores of that quantitative indicator. This is the standardized score of the positive indicator of the quantitative indicator. When the quantitative indicator is negative, the standardized score set is the standardized score of that quantitative indicator. This is the standardized score of the negative indicator of the quantitative indicator. ; For the first The first criterion level The standardized score of each quantitative indicator; The criterion-layer score set is obtained based on the standardized score set and the second weight set. ; In the formula, For the first The criterion layer score value of each criterion layer For the first The first criterion level The weight values ​​of each quantitative indicator, For the first The total number of quantitative indicators under each criterion level; The target layer score is obtained based on the score set of the evaluation dimensions and the first weight value set: ; In the formula, The target layer score is the comprehensive evaluation index for multi-element energy storage projects. For the first The weight values ​​of each criterion layer This refers to the total number of criteria layers, i.e., the total number of evaluation dimensions; In some embodiments, when the target layer score is At that time, the investment decision is a priority investment, which means that the investment decision requirements of the enterprise's energy storage project are met, and it can be included in the annual key investment plan and funds and resources are allocated with priority. When the target layer score is At that time, the investment decision is a prudent investment, which means that it meets the basic requirements for corporate energy storage project investment decisions and can be carried out according to the company's regular investment decision-making process (such as project due diligence and review meetings); When the target layer score is If the investment decision is restricted, it means that the company's investment requirements are not yet fully met. After optimization and adjustment to address the shortcomings, a new evaluation will be conducted. After optimization, the company can only participate in some low-risk market scenarios. When the target layer score is When the investment decision is negative, it means that the project does not meet the requirements for investment decisions on energy storage projects, and the investment option is directly excluded and not included in the project reserve. in, To score the target layer, The first threshold, The second threshold, The third threshold is typically the first threshold when the full score is 100. Take 90, the second threshold Take 75, the third threshold Take 60.

[0029] See Figure 2 Secondly, this invention proposes a multi-element energy storage evaluation system adapted to new power systems, which is constructed using a multi-element energy storage evaluation method adapted to new power systems, including a data acquisition unit, a weight adjustment unit, a calculation unit, and a decision-making unit. The data acquisition unit is used to acquire application scenarios and weight adjustment mechanisms, to acquire evaluation dimension sets, quantitative indicator sets and initial weight values ​​based on application scenarios, and to acquire quantitative indicator value sets based on the quantitative indicator set. The weight adjustment unit is used to obtain a first set of weight values ​​and a second set of weight values ​​based on the initial weight values ​​and the weight adjustment mechanism; The calculation unit is used to obtain the target layer score based on the set of quantitative index values, the first set of weight values, and the second set of weight values; The decision-making unit is used to make investment decisions based on the target layer score.

[0030] See Figure 3 In some embodiments, the calculation unit includes an index standardization module and a weighted calculation module; The indicator standardization module is used to obtain a standardized score set based on the indicator's full score and the set of quantified indicator values; The weighted calculation module is used to obtain the criterion layer score set based on the standardized score set and the second weight set, and to obtain the target layer score based on the evaluation dimension score set and the first weight set.

[0031] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A multi-element energy storage evaluation method adapted to new power systems, characterized in that, include: Obtain application scenarios and weight adjustment mechanisms; According to the application scenario, an evaluation dimension set, a quantitative indicator set, and initial weight values ​​are obtained. The evaluation dimension set is a collection of evaluation dimensions, and the quantitative indicator set is a collection of quantitative indicators. A set of quantitative indicator values ​​is obtained based on the set of quantitative indicators, wherein the set of quantitative indicator values ​​is a numerical set of quantitative indicator values. A first weight value set and a second weight value set are obtained based on the initial weight values ​​and the weight adjustment mechanism. The first weight value set is the set of values ​​for the first weight, and the first weight is the weight of the evaluation dimension. The second weight value set is the set of values ​​for the second weight, and the second weight is the weight of the quantitative indicator. The target layer score is obtained based on the set of quantitative index values, the first set of weight values, and the second set of weight values. Investment decisions are made based on the target layer scores.

2. The multi-element energy storage evaluation method adapted to new power systems according to claim 1, characterized in that, The target layer score is obtained based on the set of quantitative index values, the first set of weight values, and the second set of weight values, including: Obtain the set of full scores for quantitative indicators, wherein the set of full scores for quantitative indicators is a set of numbers containing the full scores of quantitative indicators; A standardized score set is obtained based on the full score of the indicator and the set of quantitative indicator values; The criterion layer score set is obtained based on the standardized score set and the second weight set; The target layer score is obtained based on the score set of the evaluation dimensions and the first weight set.

3. The multi-element energy storage evaluation method adapted to new power systems according to claim 2, characterized in that, The evaluation dimensions are technical reliability, economic profitability, environmental compliance, or market and scenario adaptability.

4. The multi-element energy storage evaluation method adapted to new power systems according to claim 3, characterized in that, When the evaluation dimension is the reliability of the technology, the set of quantitative indicators includes a performance assurance indicator group and a risk control indicator group.

5. The multi-element energy storage evaluation method adapted to new power systems according to claim 3, characterized in that, When the evaluation dimension is economic profitability, the set of quantitative indicators includes a cost control indicator group and a profitability indicator group.

6. The multi-element energy storage evaluation method adapted to new power systems according to claim 3, characterized in that, When the evaluation dimension is environmental compliance, the set of quantitative indicators includes a carbon cost indicator group and a compliance risk indicator group.

7. The multi-element energy storage evaluation method adapted to new power systems according to claim 3, characterized in that, When the evaluation dimension is the market and scenario adaptability, the quantitative indicator set includes a market return indicator group and a policy dividend indicator group.

8. The multi-element energy storage evaluation method adapted to new power systems according to claim 1, characterized in that, Obtaining the first weight value set and the second weight value set based on the initial weight values ​​and the weight adjustment mechanism includes: The system acquires preset adjustment cycles, local impact changes, and substantial impact changes; the local impact changes include any of the following: changes in power supply structure, load characteristic adjustments, or updates to regional energy storage policies. The substantial impactful changes include any one of the following: updates to evaluation dimensions, updates to indicator groups, or updates to quantitative indicators; Based on the weight adjustment conditions, and according to the preset adjustment period, local impact changes, and substantial impact changes, the initial weight values ​​are adjusted to obtain the first weight value set and the second weight value set.

9. The multi-element energy storage evaluation method for adapting to new power systems according to any one of claims 1-8, characterized in that, When the target layer score is At that time, the investment decision is a priority investment; When the target layer score is At that time, the investment decision was a prudent investment; When the target layer score is At that time, the investment decision was to restrict investment; When the target layer score is At that time, the investment decision was a negative investment; in, To score the target layer, The first threshold, The second threshold, This is the third threshold.

10. A multi-element energy storage evaluation system adapted to new power systems, constructed using the multi-element energy storage evaluation method adapted to new power systems as described in any one of claims 1-9, characterized in that, It includes a data acquisition unit, a weight adjustment unit, a calculation unit, and a decision-making unit; The data acquisition unit is used to acquire application scenarios and weight adjustment mechanisms, to acquire evaluation dimension sets, quantitative indicator sets and initial weight values ​​according to the application scenarios, and to acquire quantitative indicator value sets based on the quantitative indicator sets. The weight adjustment unit is used to obtain a first weight value set and a second weight value set according to the initial weight values ​​and the weight adjustment mechanism; The calculation unit is used to obtain the target layer score based on the set of quantitative index values, the first set of weight values, and the second set of weight values. The decision-making unit is used to obtain investment decisions based on the target layer score.

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