A method, device and equipment for processing review data of a new energy storage project

Abstract

The embodiment of the application provides a kind of new energy energy storage project's review data processing method, device and equipment, method includes: to the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data and the first intermediate energy storage power generation system full-dimensional safety protection data are verified, and compliance verification result, technical verification result, economic verification result and safety verification result are obtained;According to compliance verification result, technical verification result, economic verification result and safety verification result, obtain the processing result of the review data of new energy energy storage project.The review result quantization output can be realized by the application.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of new energy storage technology, and in particular to a method, apparatus and equipment for processing review data of new energy storage projects. Background Technology

[0002] With the development of the new energy industry, energy storage, as a core supporting facility for new energy consumption and power grid peak and frequency regulation, has seen explosive growth in the number and scale of its projects. New energy storage projects undergo multi-dimensional reviews from project initiation to grid connection and operation, generating massive amounts of review data across various categories, including compliance filing, technical parameters, economic accounting, and safety protection. This data is presented in various formats, including structured forms, unstructured documents, and semi-structured reports.

[0003] Currently, the processing of data for new energy storage project reviews primarily relies on manual methods supplemented by information technology, which presents several technical challenges: Low data classification efficiency: Manually categorizing multi-source, heterogeneous review data across compliance, technical, economic, and safety dimensions is prone to errors, time-consuming, and labor-intensive, making it unsuitable for large-scale project reviews; Lack of standardized data processing: Similar data from different sources and in different formats (such as unit energy storage cost and charge / discharge efficiency) lacks unified verification standards, resulting in poor data comparability and impacting the objectivity of review results; Limited verification logic: Traditional reviews often focus on independent verification of single indicators, failing to establish a multi-dimensional, multi-level comprehensive verification system. In particular, compliance and safety indicators lack a veto mechanism, easily leading to loopholes in project reviews; Low quantification of review results: Verification results for technical and economic indicators are mostly qualitative evaluations, lacking a standardized quantitative scoring system, making effective comparisons between different projects difficult and hindering project tiering, screening, and decision-making. Summary of the Invention

[0004] The technical problem to be solved by the embodiments of the present invention is to provide a method, device and equipment for processing review data of new energy storage projects, which can realize the quantitative output of review results and greatly improve data processing efficiency and review objectivity.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: A method for processing review data of new energy storage projects, including: Obtain review data for new energy storage projects; By analyzing the review data of the new energy storage projects, we can obtain energy power generation compliance attribute data, core technology performance data of energy storage systems, full life cycle economic data of energy storage power generation projects, and full-dimensional safety protection data of energy storage power generation systems. The energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data are standardized to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data, and the first intermediate energy storage power generation system full-dimensional safety protection data. The compliance attribute data of the first intermediate energy power generation, the core technical performance data of the first intermediate energy storage system, the economic data of the first intermediate energy storage power generation project throughout its entire life cycle, and the safety protection data of the first intermediate energy storage power generation system in all dimensions are verified to obtain compliance verification results, technical verification results, economic verification results, and safety verification results. Based on the compliance verification results, technical verification results, economic verification results, and safety verification results, the processing results of the review data for the new energy storage project are obtained.

[0006] Optionally, the review data of the new energy storage project can be analyzed to obtain energy generation compliance attribute data, core technology performance data of the energy storage system, full life-cycle economic data of the energy storage power generation project, and full-dimensional safety protection data of the energy storage power generation system, including: The review data of the new energy storage project is subjected to structured analysis to obtain a structured review data set; Based on the matching degree between the structured review data set and each tag in the preset classification tag set, the tag of each structured review data in the structured review data set is determined; Based on the tags of each structured review data in the structured review data set, each structured review data is divided into energy power generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data.

[0007] Optionally, the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project lifecycle economic data, and energy storage power generation system full-dimensional security protection data are standardized to obtain first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project lifecycle economic data, and first intermediate energy storage power generation system full-dimensional security protection data, including: Identify the types of each data item in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data; Based on the types of the data, the data in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data are standardized to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data, and the first intermediate energy storage power generation system full-dimensional safety protection data.

[0008] Optionally, the compliance attribute data of the first intermediate energy generation is verified to obtain a compliance verification result, including: The compliance attribute data of the first intermediate energy power generation is divided into a subset of filing documents, a subset of environmental approvals, and a subset of grid connection qualifications; according to Determine the verification results of the subset of the filing documents; in, D 1 = At time 1, the verification result of the subset of filing documents was passed. D 1 = At time 0, the verification result of the subset of filing documents is "failed". check ( ) is the check function. This is a subset of the filing documents. BA i Sub-data of a subset of the filing documents i =1, 2, ..., a , a The total number of sub-data in the subset of the filing documents; according to Determine the verification results of the environmental approval subset; in, D 2 = At 1 o'clock, the verification result of the environmental approval subset was passed. D 2 = At 0:00, the verification result of the environmental approval subset was "failed". This is a subset of environmental approvals. HB j This is a subset of data from the environmental approval process. j =1, 2, ..., b , b This represents the total number of sub-data points within the environmental approval subset. according to Determine the verification results of the environmental approval subset; in, D 3 = At time 1, the verification result of the subset of grid connection qualifications was passed. D 3= At 0:00, the verification result of the subset of grid connection qualifications was "failed". For grid connection qualifications subset, BW k Subdata of the grid connection qualification subset, k =1, 2, ..., c , c The total number of sub-data for the subset of grid connection qualifications; according to The compliance verification results are obtained. in, HG= At time 1, the compliance verification result was passed. HG= At 0, the compliance verification result is "failed".

[0009] Optionally, the core technical performance data of the first intermediate energy storage system are verified to obtain technical verification results, including: The core technical performance data of the first intermediate energy storage system are divided into a subset of energy storage capacity, a subset of charge and discharge efficiency, a subset of cycle life, a subset of power response time, and a subset of energy storage converter performance. according to Determine the number of qualified energy storage capacities in the sub-data of the energy storage capacity subset; in, CN qa The energy storage capacity is the sub-data of the energy storage capacity subset. qa= 1, 2, ..., pa , pa The total number of sub-data in the energy storage capacity subset. CN min To preset the minimum threshold for energy storage capacity, CN max The preset maximum threshold for energy storage capacity; according to Determine the number of qualified charge / discharge efficiencies in the sub-data set of charge / discharge efficiency. in, CF qb The charge / discharge efficiency is the sub-data of the charge / discharge efficiency subset. qb= 1, 2, ..., pb , pb This represents the total number of sub-data points within the charge / discharge efficiency subset. CF min The minimum threshold for preset charge / discharge efficiency; according to Determine the number of subdata cycles that meet the cycle lifetime requirement within the cycle lifetime subset; in, SM qc The cycle lifetime of the sub-data in the cycle lifetime subset. qc=1, 2, ..., pc , pc This represents the total number of sub-data points within the lifetime subset. SM min The preset minimum cycle life threshold; according to Determine the number of qualified sub-power response times within the power response time subset; in, GL qd The power response time is the power response time of a subset of data within the power response time subset. qd= 1, 2, ..., pd , pd The total number of sub-data points in the power response time subset. GL max The preset maximum threshold for power response time; according to Determine the number of qualified energy storage converters in the energy storage converter performance subset; in, BL qe The energy storage converter performance is a subset of the data in the energy storage converter performance subset. qe= 1, 2, ..., pe , pe This represents the total number of sub-data points within the performance subset of the energy storage converter. BL basic To preset the rated performance of the energy storage converter, BL yz This is the allowable error for the preset energy storage converter performance; according to The technical verification results were obtained. in, JS For technical verification results, SCN This refers to the number of qualified energy storage capacities within the subset of energy storage capacity. SCF This represents the number of data points within the subset of charge / discharge efficiency that meet the required standards. SSM This represents the number of data points in the subset of cycle lifetimes that have passed the cycle lifetime test. SGL This represents the number of sub-power response times that meet the requirements within the power response time subset. SBL This refers to the number of energy storage converters that meet the performance standards within the performance subset of energy storage converters. w 1 is the first weighting coefficient. w 2 is the second weighting coefficient. w 3 is the third weighting coefficient. w 4 is the fourth weighting coefficient. w 5 is the fifth weighting coefficient.

[0010] Optionally, the economic data of the first intermediate energy storage power generation project throughout its entire life cycle are verified to obtain economic verification results, including: The economic data of the first intermediate energy storage power generation project throughout its entire life cycle are divided into a subset of unit energy storage cost, a subset of return on investment, a subset of static investment payback period, a subset of cost per kilowatt-hour, and a subset of operation and maintenance cost. according to Determine the number of qualified sub-data units for energy storage cost within the unit energy storage cost subset; in, DW qf The unit energy storage cost is the sub-data within the unit energy storage cost subset. qf= 1, 2, ..., pf , pf The total number of sub-data in the unit energy storage cost subset. DW max The maximum threshold for the unit energy storage cost is preset. according to Determine the number of qualified sub-data points for return on investment within the return on investment subset; in, TZ qg The return on investment is the return on investment for a subset of data within the subset of return on investment. qg= 1, 2, ..., pg , pg The total number of sub-data in the investment return subset. TZ min Set a minimum threshold for the rate of return on investment; according to Determine the number of eligible sub-data points in the static payback period subset; in, JT qh The static payback period is the static payback period of a subset of data within the static payback period subset. qh= 1, 2, ..., ph , ph This represents the total number of sub-data points in the static payback period subset. JT max The maximum threshold for the static payback period is preset; according to Determine the number of qualified sub-data points for cost per kilowatt-hour within the cost per kilowatt-hour subset; in, DD qi The cost per kilowatt-hour is the cost per kilowatt-hour for a subset of data in the cost per kilowatt-hour subset. qi= 1, 2, ..., pi , pi The total number of sub-data in the cost per kilowatt-hour subset. DD maxThe preset maximum threshold for cost per kilowatt-hour; according to Determine the number of qualified sub-data operation and maintenance costs within the operation and maintenance cost subset; in, YY qj The operation and maintenance costs are the costs of the sub-data within the subset of operation and maintenance costs. qj= 1, 2, ..., ph , ph The total number of sub-data in the operation and maintenance cost subset. YY max To preset the maximum threshold for operation and maintenance costs; according to The economic verification results are obtained. in, JJ For the economic verification results, SDW This refers to the number of qualified energy storage units for the unit energy storage cost subset. STZ The number of qualified investment returns for a subset of data within the investment return subset. SJT This refers to the number of eligible data points within the static payback period subset. SDD The number of qualified cost-per-kilowatt-hours (kWh) data points within the cost-per-kilowatt-hour subset. SYY The number of qualified sub-data in the operation and maintenance cost subset. w 6 represents the six-weight coefficient. w 7 is the seventh weighting coefficient. w 8 represents the eighth weighting coefficient. w 9 is the ninth weighting coefficient. w 10 This is the tenth weighting coefficient.

[0011] Optionally, the full-dimensional security protection data of the first intermediate energy storage power generation system is verified to obtain the security verification results, including: The first intermediate energy storage power generation system's full-dimensional safety protection data is divided into a battery body safety subset, a fire protection design subset, an electrical safety subset, an operation and maintenance safety subset, and an extreme working condition protection subset; according to Determine the number of batteries that meet safety standards within the battery safety subset; in, DC qk For the battery security of the sub-data in the battery security subset, qk= 1, 2, ..., pk , pk The total number of sub-data in the battery body safety subset. DC min To preset the minimum safety threshold for the battery itself,DC max The preset maximum safety threshold for the battery itself; according to To determine the number of qualified fire protection designs among the sub-data in the fire protection design subset; in, XF ql Fire protection design for sub-data in the fire protection design subset. ql= 1, 2, ..., pl , pl The total number of sub-data in the fire protection design subset. XF min This is the preset minimum threshold for fire protection design; according to To determine the number of sub-data items that are qualified for electrical safety within the electrical safety subset; in, DQ qm For the electrical safety of sub-data in the electrical safety subset, qm= 1, 2, ..., pm , pm The total number of sub-data in the electrical safety subset. DQ min To preset the minimum electrical safety threshold, DQ max To preset the maximum electrical safety threshold; according to Determine the number of sub-data that meet the safety standards for operation and maintenance within the operation and maintenance security subset; in, YW qn For the operational security of sub-data within the operational security subset, qn= 1, 2, ..., pn , pn The total number of sub-data in the operation and maintenance security subset. YW min To preset the minimum threshold for operational and maintenance security; according to Determine the number of qualified extreme condition protection sub-data in the extreme condition protection subset; in, JD qo Extreme condition protection for sub-data within the extreme condition protection subset. qo= 1, 2, ..., po , po This represents the total number of sub-data within the extreme condition protection subset. JD min The minimum threshold for protection under extreme operating conditions is preset; according to The security verification result is obtained; in, AQ For security verification results, SDC This refers to the number of batteries that meet safety standards within the battery safety subset. SXF The number of qualified fire protection designs is a subset of the fire protection design data. SDQ The number of electrical safety qualified items in the sub-data of the electrical safety subset. SYW The number of data items that pass the operation and maintenance security assessment within the operation and maintenance security subset. SJD This represents the number of qualified extreme condition protection measures within the extreme condition protection subset. w 11 It is a six-weighted coefficient. w 12 It is the seventh weighting coefficient. w 13 This is the eighth weighting coefficient. w 14 It is the ninth weighting coefficient. w 5 is the tenth weighting coefficient.

[0012] Optionally, based on the compliance verification results, technical verification results, economic verification results, and safety verification results, the processing results of the review data for the new energy storage project are obtained, including: according to To conduct a preliminary assessment of the project review data; in, HG For compliance verification results, AQ For security verification results; Based on the preliminary review data of the projects,

[0013]

[0014] The project review data will be used to obtain a comprehensive score. in, PS The overall score is calculated based on the project review data. JS For technical verification results, JS max The maximum value of the quantized result of the technical verification. JJ For the economic verification results, JJ max The maximum value of the quantitative result of the economic verification. w 16 It has sixteen weighting coefficients. w 17 This is the seventeenth weighting coefficient. w 18 This is the eighteenth weighting coefficient. w 19 This is the nineteenth weighting coefficient; according to The final processed results of the review data for new energy storage projects are obtained. in, PS min This is the minimum passing threshold for the overall score of the project review data.

[0015] This invention provides a data processing device for reviewing new energy storage projects, comprising: The acquisition module is used to acquire review data for new energy storage projects; The control module is used to parse the review data of the new energy storage project to obtain energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data. It then standardizes these data to obtain first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project full life cycle economic data, and first intermediate energy storage power generation system full-dimensional safety protection data. Finally, it verifies these data to obtain compliance verification results, technical verification results, economic verification results, and safety verification results. Based on these results, it obtains the processing results of the review data for the new energy storage project.

[0016] Embodiments of the present invention also provide a computing device readable storage medium storing a program that, when executed by a processor, implements the method described above.

[0017] The above-described solutions of the embodiments of the present invention have at least the following beneficial effects: The above-described solution in this invention achieves standardized processing of multi-source heterogeneous data by parsing and splitting four types of core data: compliance attribute data of energy generation, core technical performance data of energy storage system, economic data of the entire life cycle of energy storage power generation project, and comprehensive security protection data of energy storage power generation system. This improves data standardization and comparability; constructs a multi-dimensional layered verification mechanism to compensate for the loopholes of traditional single verification; and achieves quantitative output of review results, significantly improving data processing efficiency and review objectivity. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the method for processing review data of new energy storage projects provided in an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of a module for processing review data of a new energy storage project provided in an embodiment of the present invention. Detailed Implementation

[0020] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0021] like Figure 1 As shown, an embodiment of the present invention provides a method for processing review data of a new energy storage project, including: Step 11: Obtain review data for new energy storage projects; Step 12: Analyze the review data of the new energy storage project to obtain energy power generation compliance attribute data, core technology performance data of the energy storage system, full life cycle economic data of the energy storage power generation project, and full-dimensional safety protection data of the energy storage power generation system; Step 13: Standardize the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data, and the first intermediate energy storage power generation system full-dimensional security protection data. Step 14: Verify the compliance attribute data of the first intermediate energy power generation, the core technical performance data of the first intermediate energy storage system, the full life cycle economic data of the first intermediate energy storage power generation project, and the full-dimensional security protection data of the first intermediate energy storage power generation system to obtain compliance verification results, technical verification results, economic verification results, and security verification results. Step 15: Based on the compliance verification results, technical verification results, economic verification results, and safety verification results, obtain the processing results of the review data for the new energy storage project.

[0022] In this embodiment, by parsing and splitting four types of core data—energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data—standardized processing of multi-source heterogeneous data is achieved, improving data standardization and comparability; a multi-dimensional layered verification mechanism is constructed to compensate for the loopholes of traditional single verification; and quantitative output of review results is achieved, significantly improving data processing efficiency and review objectivity.

[0023] In an optional embodiment of the present invention, in step 11, the review data of the new energy storage project is obtained. Specifically, the full amount of data related to the review of the new energy storage project can be collected through multiple channels such as online application system, offline document submission, and third-party testing agency interface, covering types such as structured forms, unstructured documents, and semi-structured reports. The collected raw data is preprocessed to unify the format, and invalid, duplicate, missing and abnormal data are removed to form a standardized raw data set.

[0024] This embodiment covers sources such as online applications, offline documents, and third-party interfaces, and is compatible with multiple data types including structured, unstructured, and semi-structured data. It achieves comprehensive data collection for review, avoiding data omissions and fragmented sources. Simultaneously, it performs format standardization preprocessing on the raw data, eliminating invalid, duplicate, and missing data to form a standardized raw dataset. This effectively solves the problems of fragmented, inconsistently formatted, and low-quality data from traditional manual data collection, improving data integrity and accuracy. In an optional embodiment of the present invention, step 12 involves parsing the review data of the new energy storage project to obtain energy generation compliance attribute data, core technology performance data of the energy storage system, full life-cycle economic data of the energy storage power generation project, and full-dimensional security protection data of the energy storage power generation system, including: Step 121: Perform structured parsing on the review data of the new energy storage project to obtain a structured review data set. Specifically, structured parsing can be performed on the pre-processed original review data of the new energy storage project. For unstructured document and report data, key information is extracted and converted into structured data in key-value pair format. For semi-structured report and form data, field names and data formats are standardized, and missing related information is filled in. All processed structured data is integrated and deduplicated to form a structured review data set with standardized fields and clear relationships. Step 122: Based on the matching degree between the structured review data set and each tag in the preset classification tag set, determine the tag for each structured review data in the structured review data set. Specifically, retrieve the preset classification tag set for new energy storage project review data. This tag set includes four main tags: compliance, technology, economy, and safety, as well as sub-tags such as filing documents and energy storage capacity under each main tag. Calculate the matching degree between each piece of data in the structured review data set and each tag in the tag set using text similarity, and take the tag with the highest matching degree as the unique associated tag for that piece of structured review data. Step 123: Based on the tags of each structured review data in the structured review data set, classify the structured review data into energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data. Specifically, based on the structured review data set with assigned tags, data can be classified and collected according to the main category to which the tags belong. All data with compliance main tags are integrated into energy generation compliance attribute data, technology main tag data are integrated into energy storage system core technology performance data, economic main tag data are integrated into energy storage power generation project full life cycle economic data, and safety main tag data are integrated into energy storage power generation system full-dimensional safety protection data.

[0025] In this embodiment, hierarchical parsing achieves accurate classification of review data. Structured parsing transforms multi-source, heterogeneous raw data into standardized key-value pair structured data, eliminating data redundancy and unifying data format after integration and deduplication. Based on preset tag sets and similarity-based tag matching, accurate association between data and tags is achieved, avoiding subjective biases from manual classification. Data is aggregated by main tags, quickly breaking down structured data into four core categories: compliance, technology, economics, and security. This clarifies data dimension divisions and improves the targeting and efficiency of subsequent standardization processing and verification.

[0026] In an optional embodiment of the present invention, step 13 involves standardizing the energy generation compliance attribute data, the core technology performance data of the energy storage system, the full life-cycle economic data of the energy storage power generation project, and the full-dimensional security protection data of the energy storage power generation system to obtain first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project full life-cycle economic data, and first intermediate energy storage power generation system full-dimensional security protection data, including: Step 131 involves identifying the data types of each item in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project lifecycle economic data, and energy storage power generation system all-dimensional safety protection data. Specifically, data type identification can be performed on each of the four data categories: energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project lifecycle economic data, and energy storage power generation system all-dimensional safety protection data. Through data feature extraction and type matching, data types such as numerical, text, Boolean, and time types can be distinguished. Numerical data includes quantitative indicators such as cost, efficiency, and capacity; text data includes textual information such as filing document number and approval opinions; Boolean data includes binary judgments such as qualified / unqualified; and time data includes time information such as approval date and commissioning time. This completes the accurate identification and labeling of the four data types. Step 132: Based on the types of the data, standardize the data in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project lifecycle economic data, and energy storage power generation system all-dimensional safety protection data to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project lifecycle economic data, and the first intermediate energy storage power generation system all-dimensional safety protection data. Specifically, standardization can be implemented in a targeted manner according to the type of data annotation: for numerical data, a normalization / standardization algorithm is used to unify the dimensions. The data is formatted, keywords are extracted, and standardized coding is performed on text data; Boolean data is converted to 0 / 1 standardized values; time data is standardized to a preset time format; after completing full standardization processing on four types of data—energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data—the data are integrated to form standardized and unified first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project full life cycle economic data, and first intermediate energy storage power generation system full-dimensional safety protection data.

[0027] In this embodiment, a hierarchical processing approach—first identifying and then standardizing—achieves unified standardization for four types of review data. Accurate data type identification and labeling provide a basis for targeted standardization, avoiding errors caused by homogenized processing methods. Adaptive standardization methods are employed for different data types, unifying numerical units, text formats, Boolean notations, and time specifications, eliminating format differences and dimensional barriers between multi-source data, and improving data consistency and comparability. This standardized first intermediate data lays a standardized data foundation for subsequent precise verification in compliance, technology, and other dimensions, significantly reducing data processing costs during the verification process.

[0028] In an optional embodiment of the present invention, step 14, verifying the compliance attribute data of the first intermediate energy generation to obtain a compliance verification result, includes: Step 1401: Divide the first intermediate energy power generation compliance attribute data into a subset of filing documents, a subset of environmental approvals, and a subset of grid connection qualifications; Step 1402, according to Determine the verification results of the subset of the filing documents; in, D 1 = At time 1, the verification result of the subset of filing documents was passed. D 1 = At time 0, the verification result of the subset of filing documents is "failed". check ( ) is the check function. This is a subset of the filing documents. BA i Sub-data of a subset of the filing documents i =1, 2, ..., a , a The total number of sub-data in the subset of the filing documents; Step 1403, according to Determine the verification results of the environmental approval subset; in, D 2 = At 1 o'clock, the verification result of the environmental approval subset was passed. D 2 = At 0:00, the verification result of the environmental approval subset was "failed". This is a subset of environmental approvals. HB j This is a subset of data from the environmental approval process. j =1, 2, ..., b , b This represents the total number of sub-data points within the environmental approval subset. Step 1404, according to Determine the verification results of the environmental approval subset; in, D 3 = At time 1, the verification result of the subset of grid connection qualifications was passed. D 3 = At 0:00, the verification result of the subset of grid connection qualifications was "failed". For grid connection qualifications subset, BW k Subdata of the grid connection qualification subset, k =1, 2, ..., c , c The total number of sub-data for the subset of grid connection qualifications; Step 1405, according to The compliance verification results are obtained. in, HG= At time 1, the compliance verification result was passed. HG= At 0, the compliance verification result is "failed".

[0029] In this embodiment, energy generation compliance attribute data is broken down into three core subsets: filing, environmental protection, and grid connection. A verification function is used to perform full verification of the sub-data within each subset. If any sub-data fails to meet the standard, the corresponding subset verification fails, achieving refined verification of compliance dimensions. The final compliance is determined by superimposing the verification results of the three subsets, forming a comprehensive, one-vote veto verification mechanism to strictly control the compliance bottom line of energy storage projects and avoid project risks caused by the absence of a single compliance item.

[0030] In an optional embodiment of the present invention, step 14 involves verifying the core technical performance data of the first intermediate energy storage system to obtain a technical verification result, including: Step 1406: Divide the core technical performance data of the first intermediate energy storage system into a subset of energy storage capacity, a subset of charge and discharge efficiency, a subset of cycle life, a subset of power response time, and a subset of energy storage converter performance. Step 1407, according to Determine the number of qualified energy storage capacities in the sub-data of the energy storage capacity subset; in, CN qa The energy storage capacity is the sub-data of the energy storage capacity subset. qa= 1, 2, ..., pa , pa The total number of sub-data in the energy storage capacity subset. CN min To preset the minimum threshold for energy storage capacity, CN max The preset maximum threshold for energy storage capacity; Step 1408, according to Determine the number of qualified charge / discharge efficiencies in the sub-data set of charge / discharge efficiency. in, CF qb The charge / discharge efficiency is the sub-data of the charge / discharge efficiency subset. qb= 1, 2, ..., pb , pb This represents the total number of sub-data points within the charge / discharge efficiency subset. CF min The minimum threshold for preset charge / discharge efficiency; Step 1409, according to Determine the number of subdata cycles that meet the cycle lifetime requirement within the cycle lifetime subset; in, SM qc The cycle lifetime of the sub-data in the cycle lifetime subset. qc= 1, 2, ..., pc , pc This represents the total number of sub-data points within the lifetime subset. SM min The preset minimum cycle life threshold; Step 1410, according to Determine the number of qualified sub-power response times within the power response time subset; in, GL qd The power response time is the power response time of a subset of data within the power response time subset. qd= 1, 2, ...,pd , pd The total number of sub-data points in the power response time subset. GL max The preset maximum threshold for power response time; Step 1411, according to Determine the number of qualified energy storage converters in the energy storage converter performance subset; in, BL qe The energy storage converter performance is a subset of the data in the energy storage converter performance subset. qe= 1, 2, ..., pe , pe This represents the total number of sub-data points within the performance subset of the energy storage converter. BL basic To preset the rated performance of the energy storage converter, BL yz This is the allowable error for the preset energy storage converter performance; Step 1412, according to The technical verification results were obtained. in, JS For technical verification results, SCN This refers to the number of qualified energy storage capacities within the subset of energy storage capacity. SCF This represents the number of data points within the subset of charge / discharge efficiency that meet the required standards. SSM This represents the number of data points in the subset of cycle lifetimes that have passed the cycle lifetime test. SGL This represents the number of sub-power response times that meet the requirements within the power response time subset. SBL This refers to the number of energy storage converters that meet the performance standards within the performance subset of energy storage converters. w 1 is the first weighting coefficient. w 2 is the second weighting coefficient. w 3 is the third weighting coefficient. w 4 is the fourth weighting coefficient. w 5 is the fifth weighting coefficient.

[0031] In this embodiment, the compliance of each subset of data is determined one by one according to a preset threshold, and the number of qualified data is counted. This achieves refined and standardized verification of technical indicators, avoiding the problem of missing detection for a single indicator. Quantitative technical verification results are obtained through weighted calculation. The weight coefficients can be adjusted according to the needs of energy storage projects to adapt to the technical review standards of different application scenarios, making the technical verification results more targeted and quantitatively referential, and improving the objectivity and flexibility of technical dimension review.

[0032] In an optional embodiment of the present invention, step 14 involves verifying the full life-cycle economic data of the first intermediate energy storage power generation project to obtain an economic verification result, including: The economic data of the first intermediate energy storage power generation project throughout its entire life cycle are divided into a subset of unit energy storage cost, a subset of return on investment, a subset of static investment payback period, a subset of cost per kilowatt-hour, and a subset of operation and maintenance cost. Step 1413, according to Determine the number of qualified sub-data units for energy storage cost within the unit energy storage cost subset; in, DW qf The unit energy storage cost is the sub-data within the unit energy storage cost subset. qf= 1, 2, ..., pf , pf The total number of sub-data in the unit energy storage cost subset. DW max The maximum threshold for the unit energy storage cost is preset. Step 1414, according to Determine the number of qualified sub-data points for return on investment within the return on investment subset; in, TZ qg The return on investment is the return on investment for a subset of data within the subset of return on investment. qg= 1, 2, ..., pg , pg The total number of sub-data in the investment return subset. TZ min Set a minimum threshold for the rate of return on investment; Step 1415, according to Determine the number of eligible sub-data points in the static payback period subset; in, JT qh The static payback period is the static payback period of a subset of data within the static payback period subset. qh= 1, 2, ..., ph , ph This represents the total number of sub-data points in the static payback period subset. JT max The maximum threshold for the static payback period is preset; Step 1416, according to Determine the number of qualified sub-data points for cost per kilowatt-hour within the cost per kilowatt-hour subset; in, DD qi The cost per kilowatt-hour is the cost per kilowatt-hour for a subset of data in the cost per kilowatt-hour subset. qi= 1, 2, ..., pi , piThe total number of sub-data in the cost per kilowatt-hour subset. DD max The preset maximum threshold for cost per kilowatt-hour; Step 1417, according to Determine the number of qualified sub-data operation and maintenance costs within the operation and maintenance cost subset; in, YY qj The operation and maintenance costs are the costs of the sub-data within the subset of operation and maintenance costs. qj= 1, 2, ..., ph , ph The total number of sub-data in the operation and maintenance cost subset. YY max To preset the maximum threshold for operation and maintenance costs; Step 1418, according to The economic verification results are obtained. in, JJ For the economic verification results, SDW This refers to the number of qualified energy storage units for the unit energy storage cost subset. STZ The number of qualified investment returns for a subset of data within the investment return subset. SJT This refers to the number of eligible data points within the static payback period subset. SDD The number of qualified cost-per-kilowatt-hours (kWh) data points within the cost-per-kilowatt-hour subset. SYY The number of qualified sub-data in the operation and maintenance cost subset. w 6 represents the six-weight coefficient. w 7 is the seventh weighting coefficient. w 8 represents the eighth weighting coefficient. w 9 is the ninth weighting coefficient. w 10 This is the tenth weighting coefficient.

[0033] In this embodiment, the economic data of the entire life cycle of an energy storage power generation project is broken down into five core subsets: cost, revenue, payback period, etc. The eligibility of each subset is determined according to preset thresholds, and the number of qualified subsets is counted. This achieves refined and standardized verification of economic indicators, covering the core indicators of the entire life cycle economic dimension of the energy storage project. A quantitative economic verification result is obtained through weighted calculation. The weight coefficients can be adjusted according to the project's investment positioning to adapt to the economic review standards of different investment scenarios, making the economic verification result both quantitatively referential and scenario-adaptable.

[0034] In an optional embodiment of the present invention, step 14 involves verifying the full-dimensional security protection data of the first intermediate energy storage power generation system to obtain a security verification result, including: Step 1419: Divide the full-dimensional safety protection data of the first intermediate energy storage power generation system into a battery body safety subset, a fire protection design subset, an electrical safety subset, an operation and maintenance safety subset, and an extreme working condition protection subset; Step 1420, according to Determine the number of batteries that meet safety standards within the battery safety subset; in, DC qk For the battery security of the sub-data in the battery security subset, qk= 1, 2, ..., pk , pk The total number of sub-data in the battery body safety subset. DC min To preset the minimum safety threshold for the battery itself, DC max The preset maximum safety threshold for the battery itself; Step 1421, according to To determine the number of qualified fire protection designs among the sub-data in the fire protection design subset; in, XF ql Fire protection design for sub-data in the fire protection design subset. ql= 1, 2, ..., pl , pl The total number of sub-data in the fire protection design subset. XF min This is the preset minimum threshold for fire protection design; Step 1422, according to To determine the number of sub-data items that are qualified for electrical safety within the electrical safety subset; in, DQ qm For the electrical safety of sub-data in the electrical safety subset, qm= 1, 2, ..., pm , pm The total number of sub-data in the electrical safety subset. DQ min To preset the minimum electrical safety threshold, DQ max To preset the maximum electrical safety threshold; Step 1423, according to Determine the number of sub-data that meet the safety standards for operation and maintenance within the operation and maintenance security subset; in, YW qn For the operational security of sub-data within the operational security subset, qn= 1, 2, ..., pn , pn The total number of sub-data in the operation and maintenance security subset.YW min To preset the minimum threshold for operational and maintenance security; Step 1424, according to Determine the number of qualified extreme condition protection sub-data in the extreme condition protection subset; in, JD qo Extreme condition protection for sub-data within the extreme condition protection subset. qo= 1, 2, ..., po , po This represents the total number of sub-data within the extreme condition protection subset. JD min The minimum threshold for protection under extreme operating conditions is preset; Step 1425, according to The security verification result is obtained; in, AQ For security verification results, SDC This refers to the number of batteries that meet safety standards within the battery safety subset. SXF The number of qualified fire protection designs is a subset of the fire protection design data. SDQ The number of electrical safety qualified items in the sub-data of the electrical safety subset. SYW The number of data items that pass the operation and maintenance security assessment within the operation and maintenance security subset. SJD This represents the number of qualified extreme condition protection measures within the extreme condition protection subset. w 11 It is a six-weighted coefficient. w 12 It is the seventh weighting coefficient. w 13 This is the eighth weighting coefficient. w 14 It is the ninth weighting coefficient. w 5 is the tenth weighting coefficient.

[0035] In this embodiment, the comprehensive safety protection data of the energy storage power generation system is broken down into five core subsets, including the battery itself and fire protection design, covering all safety points of the energy storage project. The compliance of each sub-data is determined according to preset thresholds, and the number of qualified data is counted, achieving refined and standardized verification of safety indicators, ensuring no safety points are missed. Quantitative safety verification results are obtained through weighted calculation, and the weight coefficients can be adjusted according to the project scenario to adapt to the safety review needs of different energy storage projects, making the safety verification both comprehensive and flexible.

[0036] In an optional embodiment of the present invention, step 15, based on the compliance verification results, technical verification results, economic verification results, and safety verification results, obtains the processing results of the review data for the new energy storage project, including: Step 151, according to To conduct a preliminary assessment of the project review data; in, HG For compliance verification results, AQ For security verification results; Step 152, based on the preliminary approved project review data...

[0037]

[0038] The project review data will be used to obtain a comprehensive score. in, PS The overall score is calculated based on the project review data. JS For technical verification results, JS max The maximum value of the quantized result of the technical verification. JJ For the economic verification results, JJ max The maximum value of the quantitative result of the economic verification. w 16 It has sixteen weighting coefficients. w 17 This is the seventeenth weighting coefficient. w 18 This is the eighteenth weighting coefficient. w 19 This is the nineteenth weighting coefficient; Step 153, according to The final processed results of the review data for new energy storage projects are obtained. in, PS min This is the minimum passing threshold for the overall score of the project review data.

[0039] In this embodiment, a two-tiered review and judgment mechanism is constructed. First, compliance and safety are set as prerequisite hard indicators; failure to meet either standard results in immediate project rejection, firmly upholding the compliance and safety bottom line of energy storage projects and mitigating core risks. For projects that pass the initial review, a weighted formula quantifies compliance, technical, economic, and safety indicators into a comprehensive score, achieving standardized and quantitative evaluation of multi-dimensional indicators. This score, combined with preset thresholds, determines the final result, making the review conclusion more objective and quantifiable. Furthermore, the weights can be flexibly adjusted to adapt to different review needs.

[0040] This invention employs multi-channel data collection and preprocessing, combining structured parsing and tag matching to achieve accurate classification and avoid human bias. Targeted standardization eliminates differences in data format and units, improving data consistency. A pre-emptive veto mechanism is implemented for compliance and security, safeguarding the core bottom line of projects. Economic data across the entire lifecycle of technology and energy storage power generation projects are quantified and weighted according to thresholds, enabling multi-dimensional quantitative assessment. A two-tiered review mechanism combines rigor and flexibility, significantly improving review efficiency, objectivity, and feasibility.

[0041] like Figure 2 As shown, this embodiment of the invention provides a data processing device 20 for reviewing new energy storage projects, comprising: Module 21 is used to acquire review data for new energy storage projects; The control module 22 is used to parse the review data of the new energy storage project to obtain energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data; it standardizes the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data to obtain first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project full life cycle economic data, and first intermediate energy storage power generation system full-dimensional safety protection data; it verifies the first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project full life cycle economic data, and first intermediate energy storage power generation system full-dimensional safety protection data to obtain compliance verification results, technical verification results, economic verification results, and safety verification results; and it obtains the processing results of the review data of the new energy storage project based on the compliance verification results, technical verification results, economic verification results, and safety verification results.

[0042] Optionally, the review data of the new energy storage project can be analyzed to obtain energy generation compliance attribute data, core technology performance data of the energy storage system, full life-cycle economic data of the energy storage power generation project, and full-dimensional safety protection data of the energy storage power generation system, including: The review data of the new energy storage project is subjected to structured analysis to obtain a structured review data set; Based on the matching degree between the structured review data set and each tag in the preset classification tag set, the tag of each structured review data in the structured review data set is determined; Based on the tags of each structured review data in the structured review data set, each structured review data is divided into energy power generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data.

[0043] Optionally, the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project lifecycle economic data, and energy storage power generation system full-dimensional security protection data are standardized to obtain first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project lifecycle economic data, and first intermediate energy storage power generation system full-dimensional security protection data, including: Identify the types of each data item in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data; Based on the types of the data, the data in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data are standardized to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data, and the first intermediate energy storage power generation system full-dimensional safety protection data.

[0044] Optionally, the compliance attribute data of the first intermediate energy generation is verified to obtain a compliance verification result, including: The compliance attribute data of the first intermediate energy power generation is divided into a subset of filing documents, a subset of environmental approvals, and a subset of grid connection qualifications; according to Determine the verification results of the subset of the filing documents; in, D 1 = At time 1, the verification result of the subset of filing documents was passed. D 1 = At time 0, the verification result of the subset of filing documents is "failed". check ( ) is the check function. This is a subset of the filing documents. BA i Sub-data of a subset of the filing documents i =1, 2, ..., a , a The total number of sub-data in the subset of the filing documents; according to Determine the verification results of the environmental approval subset; in, D 2 = At 1 o'clock, the verification result of the environmental approval subset was passed. D 2 = At 0:00, the verification result of the environmental approval subset was "failed". This is a subset of environmental approvals. HB j This is a subset of data from the environmental approval process. j =1, 2, ..., b , b This represents the total number of sub-data points within the environmental approval subset. according to Determine the verification results of the environmental approval subset; in, D 3 = At time 1, the verification result of the subset of grid connection qualifications was passed. D 3 = At 0:00, the verification result of the subset of grid connection qualifications was "failed". For grid connection qualifications subset, BW k Subdata of the grid connection qualification subset, k =1, 2, ..., c , c The total number of sub-data for the subset of grid connection qualifications; according to The compliance verification results are obtained. in, HG= At time 1, the compliance verification result was passed. HG= At 0, the compliance verification result is "failed".

[0045] Optionally, the core technical performance data of the first intermediate energy storage system are verified to obtain technical verification results, including: The core technical performance data of the first intermediate energy storage system are divided into a subset of energy storage capacity, a subset of charge and discharge efficiency, a subset of cycle life, a subset of power response time, and a subset of energy storage converter performance. according to Determine the number of qualified energy storage capacities in the sub-data of the energy storage capacity subset; in, CN qa The energy storage capacity is the sub-data of the energy storage capacity subset. qa= 1, 2, ..., pa , pa The total number of sub-data in the energy storage capacity subset. CN min To preset the minimum threshold for energy storage capacity,CN max The preset maximum threshold for energy storage capacity; according to Determine the number of qualified charge / discharge efficiencies in the sub-data set of charge / discharge efficiency. in, CF qb The charge / discharge efficiency is the sub-data of the charge / discharge efficiency subset. qb= 1, 2, ..., pb , pb This represents the total number of sub-data points within the charge / discharge efficiency subset. CF min The minimum threshold for preset charge / discharge efficiency; according to Determine the number of subdata cycles that meet the cycle lifetime requirement within the cycle lifetime subset; in, SM qc The cycle lifetime of the sub-data in the cycle lifetime subset. qc= 1, 2, ..., pc , pc This represents the total number of sub-data points within the lifetime subset. SM min The preset minimum cycle life threshold; according to Determine the number of qualified sub-power response times within the power response time subset; in, GL qd The power response time is the power response time of a subset of data within the power response time subset. qd= 1, 2, ..., pd , pd The total number of sub-data points in the power response time subset. GL max The preset maximum threshold for power response time; according to Determine the number of qualified energy storage converters in the energy storage converter performance subset; in, BL qe The energy storage converter performance is a subset of the data in the energy storage converter performance subset. qe= 1, 2, ..., pe , pe This represents the total number of sub-data points within the performance subset of the energy storage converter. BL basic To preset the rated performance of the energy storage converter, BL yz This is the allowable error for the preset energy storage converter performance; according to The technical verification results were obtained. in, JS For technical verification results, SCN This refers to the number of qualified energy storage capacities within the subset of energy storage capacity. SCF This represents the number of data points within the subset of charge / discharge efficiency that meet the required standards. SSM This represents the number of data points in the subset of cycle lifetimes that have passed the cycle lifetime test. SGL This represents the number of sub-power response times that meet the requirements within the power response time subset. SBL This refers to the number of energy storage converters that meet the performance standards within the performance subset of energy storage converters. w 1 is the first weighting coefficient. w 2 is the second weighting coefficient. w 3 is the third weighting coefficient. w 4 is the fourth weighting coefficient. w 5 is the fifth weighting coefficient.

[0046] Optionally, the economic data of the first intermediate energy storage power generation project throughout its entire life cycle are verified to obtain economic verification results, including: The economic data of the first intermediate energy storage power generation project throughout its entire life cycle are divided into a subset of unit energy storage cost, a subset of return on investment, a subset of static investment payback period, a subset of cost per kilowatt-hour, and a subset of operation and maintenance cost. according to Determine the number of qualified sub-data units for energy storage cost within the unit energy storage cost subset; in, DW qf The unit energy storage cost is the sub-data within the unit energy storage cost subset. qf= 1, 2, ..., pf , pf The total number of sub-data in the unit energy storage cost subset. DW max The maximum threshold for the unit energy storage cost is preset. according to Determine the number of qualified sub-data points for return on investment within the return on investment subset; in, TZ qg The return on investment is the return on investment for a subset of data within the subset of return on investment. qg= 1, 2, ..., pg , pg The total number of sub-data in the investment return subset. TZ min Set a minimum threshold for the rate of return on investment; according to Determine the number of eligible sub-data points in the static payback period subset; in, JT qh The static payback period is the static payback period of a subset of data within the static payback period subset. qh= 1, 2, ..., ph , ph This represents the total number of sub-data points in the static payback period subset. JT max The maximum threshold for the static payback period is preset; according to Determine the number of qualified sub-data points for cost per kilowatt-hour within the cost per kilowatt-hour subset; in, DD qi The cost per kilowatt-hour is the cost per kilowatt-hour for a subset of data in the cost per kilowatt-hour subset. qi= 1, 2, ..., pi , pi The total number of sub-data in the cost per kilowatt-hour subset. DD max The preset maximum threshold for cost per kilowatt-hour; according to Determine the number of qualified sub-data operation and maintenance costs within the operation and maintenance cost subset; in, YY qj The operation and maintenance costs are the costs of the sub-data within the subset of operation and maintenance costs. qj= 1, 2, ..., ph , ph The total number of sub-data in the operation and maintenance cost subset. YY max To preset the maximum threshold for operation and maintenance costs; according to The economic verification results are obtained. in, JJ For the economic verification results, SDW This refers to the number of qualified energy storage units for the unit energy storage cost subset. STZ The number of qualified investment returns for a subset of data within the investment return subset. SJT This refers to the number of eligible data points within the static payback period subset. SDD The number of qualified cost-per-kilowatt-hours (kWh) data points within the cost-per-kilowatt-hour subset. SYY The number of qualified sub-data in the operation and maintenance cost subset. w 6 represents the six-weight coefficient. w 7 is the seventh weighting coefficient. w 8 represents the eighth weighting coefficient. w 9 is the ninth weighting coefficient. w 10 This is the tenth weighting coefficient.

[0047] Optionally, the full-dimensional security protection data of the first intermediate energy storage power generation system is verified to obtain the security verification results, including: The first intermediate energy storage power generation system's full-dimensional safety protection data is divided into a battery body safety subset, a fire protection design subset, an electrical safety subset, an operation and maintenance safety subset, and an extreme working condition protection subset; according to Determine the number of batteries that meet safety standards within the battery safety subset; in, DC qk For the battery security of the sub-data in the battery security subset, qk= 1, 2, ..., pk , pk The total number of sub-data in the battery body safety subset. DC min To preset the minimum safety threshold for the battery itself, DC max The preset maximum safety threshold for the battery itself; according to To determine the number of qualified fire protection designs among the sub-data in the fire protection design subset; in, XF ql Fire protection design for sub-data in the fire protection design subset. ql= 1, 2, ..., pl , pl The total number of sub-data in the fire protection design subset. XF min This is the preset minimum threshold for fire protection design; according to To determine the number of sub-data items that are qualified for electrical safety within the electrical safety subset; in, DQ qm For the electrical safety of sub-data in the electrical safety subset, qm= 1, 2, ..., pm , pm The total number of sub-data in the electrical safety subset. DQ min To preset the minimum electrical safety threshold, DQ max To preset the maximum electrical safety threshold; according to Determine the number of sub-data that meet the safety standards for operation and maintenance within the operation and maintenance security subset; in, YW qn For the operational security of sub-data within the operational security subset, [[ID=305qn= 1, 2, ...,pn , pn The total number of sub-data in the operation and maintenance security subset. YW min To preset the minimum threshold for operational and maintenance security; according to Determine the number of qualified extreme condition protection sub-data in the extreme condition protection subset; in, JD qo Extreme condition protection for sub-data within the extreme condition protection subset. qo= 1, 2, ..., po , po This represents the total number of sub-data within the extreme condition protection subset. JD min The minimum threshold for protection under extreme operating conditions is preset; according to The security verification result is obtained; in, AQ For security verification results, SDC This refers to the number of batteries that meet safety standards within the battery safety subset. SXF The number of qualified fire protection designs is a subset of the fire protection design data. SDQ The number of electrical safety qualified items in the sub-data of the electrical safety subset. SYW The number of data items that pass the operation and maintenance security assessment within the operation and maintenance security subset. SJD This represents the number of qualified extreme condition protection measures within the extreme condition protection subset. w 11 It is a six-weighted coefficient. w 12 It is the seventh weighting coefficient. w 13 This is the eighth weighting coefficient. w 14 It is the ninth weighting coefficient. w 5 is the tenth weighting coefficient.

[0048] Optionally, based on the compliance verification results, technical verification results, economic verification results, and safety verification results, the processing results of the review data for the new energy storage project are obtained, including: according to To conduct a preliminary assessment of the project review data; in, HG For compliance verification results, AQ For security verification results; Based on the preliminary review data of the projects,

[0049]

[0050] The project review data will be used to obtain a comprehensive score. in, PS The overall score is calculated based on the project review data. JS For technical verification results, JS max The maximum value of the quantized result of the technical verification. JJ For the economic verification results, JJ max The maximum value of the quantitative result of the economic verification. w 16 It has sixteen weighting coefficients. w 17 This is the seventeenth weighting coefficient. w 18 This is the eighteenth weighting coefficient. w 19 This is the nineteenth weighting coefficient; according to The final processed results of the review data for new energy storage projects are obtained. in, PS min This is the minimum passing threshold for the overall score of the project review data.

[0051] It should be noted that this device is a device corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0052] Embodiments of the present invention also provide a computing device, including: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0053] Embodiments of the present invention also provide a computing device readable storage medium storing instructions that, when executed on a computing device, cause the computing device to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0054] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computing device software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0055] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0056] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0057] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0058] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0059] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computing device-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computing device software product is stored in a storage medium and includes several instructions to cause a computing device (which may be a personal computing device, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0060] Furthermore, it should be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above-described series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve using basic programming skills after reading the description of the present invention.

[0061] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0062] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for processing review data of new energy storage projects, characterized in that, include: Obtain review data for new energy storage projects; By analyzing the review data of the new energy storage projects, we can obtain energy power generation compliance attribute data, core technology performance data of energy storage systems, full life cycle economic data of energy storage power generation projects, and full-dimensional safety protection data of energy storage power generation systems. The energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data are standardized to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data, and the first intermediate energy storage power generation system full-dimensional safety protection data. The compliance attribute data of the first intermediate energy power generation, the core technical performance data of the first intermediate energy storage system, the economic data of the first intermediate energy storage power generation project throughout its entire life cycle, and the safety protection data of the first intermediate energy storage power generation system in all dimensions are verified to obtain compliance verification results, technical verification results, economic verification results, and safety verification results. Based on the compliance verification results, technical verification results, economic verification results, and safety verification results, the processing results of the review data for the new energy storage project are obtained.

2. The method for processing review data of new energy storage projects according to claim 1, characterized in that, Analyzing the review data of the aforementioned new energy storage projects yields energy generation compliance attribute data, core technology performance data of the energy storage system, full life-cycle economic data of the energy storage power generation project, and comprehensive safety protection data of the energy storage power generation system, including: The review data of the new energy storage project is subjected to structured analysis to obtain a structured review data set; Based on the matching degree between the structured review data set and each tag in the preset classification tag set, the tag of each structured review data in the structured review data set is determined; Based on the tags of each structured review data in the structured review data set, each structured review data is divided into energy power generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data.

3. The method for processing review data of new energy storage projects according to claim 1, characterized in that, The energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data are standardized to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data, and the first intermediate energy storage power generation system full-dimensional security protection data, including: Identify the types of each data item in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional security protection data; Based on the types of the data, the data in the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data are standardized to obtain the first intermediate energy generation compliance attribute data, the first intermediate energy storage system core technology performance data, the first intermediate energy storage power generation project full life cycle economic data, and the first intermediate energy storage power generation system full-dimensional safety protection data.

4. The method for processing review data of new energy storage projects according to claim 1, characterized in that, The compliance attribute data of the first intermediate energy generation is verified to obtain the compliance verification results, including: The compliance attribute data of the first intermediate energy power generation is divided into a subset of filing documents, a subset of environmental approvals, and a subset of grid connection qualifications; according to Determine the verification results of the subset of the filing documents; in, D 1 = At time 1, the verification result of the subset of filing documents was passed. D 1 = At time 0, the verification result of the subset of filing documents is "failed". check ( ) is the check function. This is a subset of the filing documents. BA i Subdata of a subset of the filing documents i =1, 2, ..., a , a The total number of sub-data in the subset of the filing documents; according to Determine the verification results of the environmental approval subset; in, D 2 = At 1 o'clock, the verification result of the environmental approval subset was passed. D 2 = At 0:00, the verification result of the environmental approval subset was "failed". This is a subset of environmental approvals. HB j This is a subset of data from the environmental approval process. j =1, 2, ..., b , b This represents the total number of sub-data points within the environmental approval subset. according to Determine the verification results of the environmental approval subset; in, D 3 = At time 1, the verification result of the subset of grid connection qualifications was passed. D 3 = At 0:00, the verification result of the subset of grid connection qualifications was "failed". For grid connection qualifications subset, BW k Subdata of the grid connection qualification subset, k =1, 2, ..., c , c The total number of sub-data for the subset of grid connection qualifications; according to The compliance verification results are obtained. in, HG= At time 1, the compliance verification result was passed. HG= At 0, the compliance verification result is "failed".

5. The method for processing review data of new energy storage projects according to claim 1, characterized in that, The core technical performance data of the first intermediate energy storage system were verified, and the technical verification results were obtained, including: The core technical performance data of the first intermediate energy storage system are divided into a subset of energy storage capacity, a subset of charge and discharge efficiency, a subset of cycle life, a subset of power response time, and a subset of energy storage converter performance. according to Determine the number of qualified energy storage capacities in the sub-data of the energy storage capacity subset; in, CN qa The energy storage capacity is the sub-data of the energy storage capacity subset. qa= 1, 2, ..., pa , pa The total number of sub-data in the energy storage capacity subset. CN min To preset the minimum threshold for energy storage capacity, CN max The preset maximum threshold for energy storage capacity; according to Determine the number of qualified charge / discharge efficiencies in the subset of charge / discharge efficiency data. in, CF qb The charge / discharge efficiency is the sub-data of the charge / discharge efficiency subset. qb= 1, 2, ..., pb , pb This represents the total number of sub-data points within the charge / discharge efficiency subset. CF min The preset minimum threshold for charge / discharge efficiency; according to Determine the number of subdata cycles that meet the cycle lifetime requirement within the cycle lifetime subset; in, SM qc The cycle lifetime of the sub-data in the cycle lifetime subset. qc= 1, 2, ..., PC , PC This represents the total number of sub-data points within the lifetime subset. SM min The preset minimum cycle life threshold; according to Determine the number of qualified sub-power response times within the power response time subset; in, GL qd The power response time is the power response time of a subset of data within the power response time subset. qd= 1, 2, ..., pd , pd The total number of sub-data points in the power response time subset. GL max The preset maximum threshold for power response time; according to Determine the number of qualified energy storage converters in the energy storage converter performance subset; in, BL qe The energy storage converter performance is a subset of the data in the energy storage converter performance subset. qe= 1, 2, ..., PE , PE This represents the total number of sub-data points within the performance subset of the energy storage converter. BL basic To preset the rated performance of the energy storage converter, BL yz This is the allowable error for the preset energy storage converter performance; according to The technical verification results were obtained. in, JS For technical verification results, SCN This refers to the number of qualified energy storage capacities within the subset of energy storage capacity. SCF This represents the number of data points within the subset of charge / discharge efficiency that meet the required standards. SSM This represents the number of data points in the subset of cycle lifetimes that have passed the cycle lifetime test. SGL This represents the number of sub-power response times that meet the requirements within the power response time subset. SBL This refers to the number of energy storage converters that meet the performance standards within the performance subset of energy storage converters. w 1 is the first weighting coefficient. w 2 is the second weighting coefficient. w 3 is the third weighting coefficient. w 4 is the fourth weighting coefficient. w 5 is the fifth weighting coefficient.

6. The method for processing review data of new energy storage projects according to claim 1, characterized in that, The economic data of the first intermediate energy storage power generation project throughout its entire life cycle were verified, and the economic verification results were obtained, including: The economic data of the first intermediate energy storage power generation project throughout its entire life cycle are divided into a subset of unit energy storage cost, a subset of return on investment, a subset of static investment payback period, a subset of cost per kilowatt-hour, and a subset of operation and maintenance cost. according to Determine the number of qualified sub-data units for energy storage cost within the unit energy storage cost subset; in, DW qf The unit energy storage cost is the sub-data within the unit energy storage cost subset. qf= 1, 2, ..., pf , pf The total number of sub-data in the unit energy storage cost subset. DW max The maximum threshold for the unit energy storage cost is preset. according to Determine the number of qualified sub-data points for return on investment within the return on investment subset; in, TZ qg The return on investment is the return on investment for a subset of data within the subset of return on investment. qg= 1, 2, ..., pg , pg The total number of sub-data in the ROI subset. TZ min Set a minimum threshold for the preset rate of return on investment; according to Determine the number of eligible sub-data points in the static payback period subset; in, JT qh The static payback period is the static payback period of a subset of data within the static payback period subset. qh= 1, 2, ..., ph , ph This represents the total number of sub-data points in the static payback period subset. JT max The maximum threshold for the static payback period is preset; according to Determine the number of qualified sub-data points for cost per kilowatt-hour within the cost per kilowatt-hour subset; in, DD qi The cost per kilowatt-hour is the cost per kilowatt-hour for a subset of data in the cost per kilowatt-hour subset. qi= 1, 2, ..., pi , pi The total number of sub-data in the cost per kilowatt-hour subset. DD max The preset maximum threshold for cost per kilowatt-hour; according to Determine the number of qualified sub-data operation and maintenance costs within the operation and maintenance cost subset; in, YY qj The operation and maintenance costs are the costs of the sub-data within the subset of operation and maintenance costs. qj= 1, 2, ..., ph , ph The total number of sub-data in the operation and maintenance cost subset. YY max To preset the maximum threshold for operation and maintenance costs; according to The economic verification results are obtained. in, JJ For the economic verification results, SDW This refers to the number of qualified energy storage units for the unit energy storage cost subset. STZ The number of qualified investment returns for a subset of data within the investment return subset. SJT This refers to the number of eligible data points within the static payback period subset. SDD The number of qualified cost-per-kilowatt-hours (kWh) data points within the cost-per-kilowatt-hour subset. SYY The number of qualified sub-data in the operation and maintenance cost subset. w 6 represents the six-weight coefficient. w 7 is the seventh weighting coefficient. w 8 represents the eighth weighting coefficient. w 9 is the ninth weighting coefficient. w 10 This is the tenth weighting coefficient.

7. The method for processing review data of new energy storage projects according to claim 1, characterized in that, The safety protection data of the first intermediate energy storage power generation system were verified in all dimensions to obtain the safety verification results, including: The first intermediate energy storage power generation system's full-dimensional safety protection data is divided into a battery body safety subset, a fire protection design subset, an electrical safety subset, an operation and maintenance safety subset, and an extreme working condition protection subset; according to Determine the number of batteries that meet safety standards within the battery safety subset; in, DC qk For the battery security of the sub-data in the battery security subset, qk= 1, 2, ..., pk , pk The total number of sub-data in the battery body safety subset. DC min To preset the minimum safety threshold for the battery itself, DC max The preset maximum safety threshold for the battery itself; according to To determine the number of qualified fire protection designs among the sub-data in the fire protection design subset; in, XF ql Fire protection design for sub-data in the fire protection design subset. ql= 1, 2, ..., pl , pl The total number of sub-data in the fire protection design subset. XF min This is the preset minimum threshold for fire protection design; according to Determine the number of electrical safety qualified sub-data in the electrical safety subset; in, DQ qm For the electrical safety of sub-data in the electrical safety subset, qm= 1, 2, ..., pm , pm The total number of sub-data in the electrical safety subset. DQ min To preset the minimum electrical safety threshold, DQ max To preset the maximum electrical safety threshold; according to Determine the number of sub-data that meet the safety standards for operation and maintenance within the operation and maintenance security subset; in, YW qn For the operational security of sub-data within the operational security subset, qn= 1, 2, ..., pn , pn The total number of sub-data in the operation and maintenance security subset. YW min To preset the minimum threshold for operational and maintenance security; according to Determine the number of qualified extreme condition protection sub-data in the extreme condition protection subset; in, JD qo Extreme condition protection for sub-data within the extreme condition protection subset. qo= 1, 2, ..., po , po This represents the total number of sub-data within the extreme condition protection subset. JD min The minimum threshold for protection under extreme working conditions is preset; according to The security verification result is obtained; in, AQ For security verification results, SDC This refers to the number of batteries that meet safety standards within the battery safety subset. SXF The number of qualified fire protection designs is a subset of the fire protection design data. SDQ The number of electrical safety qualified items in the sub-data of the electrical safety subset. SYW The number of data items that pass the operation and maintenance security assessment within the operation and maintenance security subset. SJD This represents the number of qualified extreme condition protection measures within the extreme condition protection subset. w 11 It is a six-weighted coefficient. w 12 It is the seventh weighting coefficient. w 13 This is the eighth weighting coefficient. w 14 It is the ninth weighting coefficient. w 5 is the tenth weighting coefficient.

8. The method for processing review data of new energy storage projects according to claim 1, characterized in that, Based on the compliance verification results, technical verification results, economic verification results, and safety verification results, the processing results of the review data for the new energy storage project are obtained, including: according to To conduct a preliminary assessment of the project review data; in, HG For compliance verification results, AQ For security verification results; Based on the preliminary review data of the projects, Obtain the overall score from the project review data; in, PS The overall score is calculated based on the project review data. JS For technical verification results, JS max The maximum value of the quantized result of the technical verification. JJ For the economic verification results, JJ max The maximum value of the quantitative result of the economic verification. w 16 It has sixteen weighting coefficients. w 17 It is the seventeenth weighting coefficient. w 18 This is the eighteenth weighting coefficient. w 19 This is the nineteenth weighting coefficient; according to The final processed results of the review data for new energy storage projects are obtained. in, PS min This is the minimum passing threshold for the overall score of the project review data.

9. A device for processing review data of a new energy storage project, characterized in that, include: The acquisition module is used to acquire review data for new energy storage projects; The control module is used to parse the review data of the new energy storage project to obtain energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data; it standardizes the energy generation compliance attribute data, energy storage system core technology performance data, energy storage power generation project full life cycle economic data, and energy storage power generation system full-dimensional safety protection data to obtain first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project full life cycle economic data, and first intermediate energy storage power generation system full-dimensional safety protection data; it verifies the first intermediate energy generation compliance attribute data, first intermediate energy storage system core technology performance data, first intermediate energy storage power generation project full life cycle economic data, and first intermediate energy storage power generation system full-dimensional safety protection data to obtain compliance verification results, technical verification results, economic verification results, and safety verification results. Based on the compliance verification results, technical verification results, economic verification results, and safety verification results, the processing results of the review data for the new energy storage project are obtained.

10. A computing device readable storage medium, characterized in that, The computing device readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 8.

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