Method for collecting investment cost of main project in construction period of photovoltaic station

Abstract

The invention discloses a photovoltaic station construction period main project investment cost collection method, and particularly relates to the technical field of photovoltaic station construction management, and the method comprises the following steps: 1, building a standard division rule of cost collection items, and determining a cost collection list; step 2, establishing an association relationship between the cost collection list and each type of business data; 3, executing automatic collection of the investment cost on the cost collection item to obtain an automatic collection list; 4, performing quality verification on the target collection items in the automatic collection list, and summarizing obtained quality verification results to obtain a quality verification list; 5, matching each item of quality verification with a preset construction acceptance policy form, and executing a construction acceptance policy; the system can achieve the comprehensive management, monitoring and automatic collection of the investment cost of the main project in the construction period of the photovoltaic station, facilitates the improvement of the project management level and management efficiency, guarantees the completion of the project according to the quality, and achieves an expected target.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power plant construction and management technology, and more specifically, to a method for collecting investment costs of the main project during the construction period of a photovoltaic power plant. Background Technology

[0002] Photovoltaic power plant construction typically has tight deadlines. Because the engineering technology is not particularly complex, the rush to meet deadlines often leads to insufficient attention to documentation and paperwork. This results in significant omissions or arbitrariness in the collection of data and documents related to investment cost aggregation throughout the entire process, from design and bidding to construction, inspection, and settlement. Consequently, when the project is completed, the construction unit often lacks necessary calculation data and supporting materials to aggregate the main project's investment costs, making the aggregation process difficult. Furthermore, traditional cost aggregation methods are somewhat arbitrary in their granularity, often depending on the experience of those who formulate the relevant rules, lacking unified standards. Some projects even fail to define cost aggregation items in the early stages, making early cost aggregation even more difficult later. Even when some construction units require all participating units to collect, organize, and archive data and documents related to cost aggregation from the start of main construction, the workload of collection and manual organization remains substantial. Moreover, this organization process can generally only be carried out after each contractor's settlement, resulting in very low levels of proactive cooperation from contractors in reality. Therefore, it is particularly important to standardize the cost collection granularity and collect the investment costs of the main project of photovoltaic power stations simply, quickly and accurately without increasing the workload of the contractor. Here, a method for collecting the investment costs of the main project during the construction period of photovoltaic power stations is proposed. Summary of the Invention

[0003] To achieve the above objectives, the present invention provides the following technical solution:

[0004] A method for collecting investment costs of the main project during the construction period of a photovoltaic power station includes the following steps:

[0005] Step 1: Establish standard rules for classifying expense items and determine the expense collection list;

[0006] Step 2: Establish the relationship between the expense collection list and various business data;

[0007] Step 3: Automatically aggregate investment costs under the cost aggregation item to obtain an automatic aggregation list;

[0008] Step 4: Perform quality verification on the target collection items in the automatically collected list in Step 3, and summarize the quality verification results to obtain a quality verification list;

[0009] Step 5: Match each quality verification item in the quality verification checklist with the preset construction acceptance strategy form and execute the corresponding preset construction acceptance strategy.

[0010] In a preferred embodiment, step one involves establishing standard rules for classifying cost items and determining that the cost collection list refers to:

[0011] The initial minimum aggregation granularity of each business item in the main project of this photovoltaic power station construction period is collected separately. A standard aggregation granularity is established for the main project of this photovoltaic power station construction period. If the initial minimum aggregation granularity of the target business item is lower than the standard aggregation granularity, the standard aggregation granularity is set as the latest minimum aggregation granularity of the target business item. If the initial minimum aggregation granularity of the target business item is greater than or equal to the standard aggregation granularity, the initial minimum aggregation granularity of the target business item is set as the latest minimum aggregation granularity of the target business item. Then, each business item is divided into aggregation levels to obtain multiple cost aggregation items. According to the division results, a corresponding tag set is preset for each cost aggregation at each level. Then, all tag sets are summarized and a cost aggregation list is established according to the aggregation level division relationship of their respective businesses.

[0012] In a preferred embodiment, step two, establishing the association between the cost collection list and various types of business data, refers to: after the cost collection list is established, establishing the association between various types of business data and cost units, including the association with the budget item, the association with the contract quantity, the association with the construction drawings, the association with the construction unit and its detailed design, and the association with the quality unit.

[0013] In a preferred embodiment, in step three, the execution investment cost refers to:

[0014] The collection of investment costs for the main project during the construction period of a photovoltaic power station includes:

[0015] Collection of various costs: estimated cost collection, committed cost collection, output value collection, and actual expense collection;

[0016] Collection of various cost support data: collection of design data, collection of construction data, collection of quality data, and collection of measurement data.

[0017] In a preferred embodiment, in step three, the collection of investment costs for the main project during the construction period of the photovoltaic power station follows the following logic:

[0018] Retrieve the set of all tags for the collection target in the cost collection list;

[0019] The aggregation similarity between two adjacent aggregation granularities is then filtered sequentially, starting with the largest aggregation granularity and ending with the smallest aggregation granularity.

[0020] The tag set of two adjacent tag sets at a higher tag set level is defined as the main set, and the tag set at a lower tag set level is defined as the secondary set. The main set is compared with multiple secondary sets using a similarity calculation method to obtain the similarity values ​​between the main set and multiple secondary sets. Then, these similarity values ​​are compared with a preset similarity threshold. The secondary sets corresponding to similarity values ​​greater than or equal to the similarity threshold are retained, and the remaining secondary sets are removed. All the retained secondary sets and the main set constitute a membership group of the tag set at the tag set level of the main set.

[0021] By summarizing all the subordinate groups, an automatic target aggregation list is obtained.

[0022] In a preferred embodiment, obtaining the similarity values ​​between the main set and the multiple subordinate sets using a similarity calculation method means:

[0023] Obtain similar label data from the label set of the main set and use it as the first vector. Obtain similar label data from the label sets of multiple secondary sets and use it as the second vector. Calculate the cosine similarity between the first vector and the multiple second vectors respectively.

[0024] In a preferred embodiment, step four, which involves performing quality verification on the target collection items in the automatically collected list from step three, refers to:

[0025] For each membership group, quality verification is performed. The verification logic is as follows: obtain the cost data of all slave sets in the membership group and label them as CFi; obtain the preset cost coefficient FXi corresponding to the cost data CFi of all slave sets; and obtain the standard cost data corresponding to the cost data CFi of all slave sets and label them as BFi. Then, calculate the quality verification value of the membership group. ZLi is the quality verification value of the subordinate relationship group. Then, the quality verification value ZLi of the subordinate relationship group is compared with the preset verification threshold. If the quality verification value ZLi of the subordinate relationship group is less than or equal to the preset verification threshold, the subordinate relationship group passes the acceptance test. If the quality verification value ZLi of the subordinate relationship group is greater than the preset verification threshold, the subordinate relationship group fails the acceptance test.

[0026] The technical effects and advantages of this invention are as follows:

[0027] This invention, by establishing standardized classification rules and an automatic collection mechanism, can effectively reduce human error and omissions, improving the accuracy and reliability of cost collection. The automated collection method significantly saves human resources and time, enabling rapid and efficient collection of investment costs and improving cost management efficiency. Effective collection and management of investment costs allows for timely understanding of project fund usage and progress, optimizing resource allocation and utilization, and ensuring effective investment utilization. The implementation of quality verification checklists and construction acceptance strategies allows for quality verification and supervision of collected cost data, ensuring data accuracy and reliability, and strengthening project quality control and supervision. This method enables comprehensive management and monitoring of investment costs for the main construction phase of photovoltaic power plants, helping to improve project management level and efficiency, ensuring the project is completed on time and achieves its expected goals. Attached Figure Description

[0028] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0029] Figure 1 This is a schematic diagram illustrating a method for collecting investment costs of the main project during the construction period of a photovoltaic power station. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0031] Example 1

[0032] A method for collecting investment costs of the main project during the construction period of a photovoltaic power station includes the following steps:

[0033] Step 1: Establish standard rules for classifying cost items and determine the cost collection list. Cost collection involves data and information related to business processes such as budgeting, design, bidding, construction, quality, and settlement. This involves a large amount of data and requires a unified collection or statistical standard. However, in current practice, the execution units for each of these business processes are different, as detailed below:

[0034] Preliminary cost estimation design generally focuses on the final functional building structure of the project, involving the design of engineering quantities and costs. For example, it might design the quantities and costs of a specific access road, the civil engineering portion of a substation, or the quantities and costs of power generation components in a photovoltaic array. Preliminary cost estimation data is hierarchical; the lowest-level estimates can be as detailed as the amount of concrete and steel reinforcement needed for the substation's civil engineering. Directly using the finest-grained estimates as cost aggregation items results in excessively fine granularity and a massive amount of data processing.

[0035] In bidding design, the engineering quantity data is generally based on the budget data and divided according to the bidding section. The engineering quantity data in the design results is basically the same as the data under a certain branch in the budget data. The final granularity will also be down to the point where a certain part needs a certain amount of concrete and photovoltaic panels. This granularity is too detailed for cost collection. The engineering quantity results of the bidding design will eventually be transformed into the bill of quantities in the signed contract.

[0036] Construction drawing design is a refinement of the preliminary design, detailing the specific processes for particular parts. The granularity is similar to that of the tender design. During actual construction, the construction drawings are used to further refine the design of specific construction areas. More detailed construction units are defined based on construction techniques, site limitations, construction sequence, and structural characteristics to ensure orderly work by each construction team. For example, in photovoltaic module installation, a row of photovoltaic arrays is typically considered a single construction unit, with very fine granularity, sometimes even finer than the contract quantity. Quality assessment is generally based on a fully deliverable functional or structural component, ensuring that a complete deliverable product is achieved upon successful unit acceptance. For instance, the overall acceptance of a photovoltaic array is only conducted after the foundations, supports, photovoltaic panels, inverters, and connecting lines of a row of power generation modules are all completed. The granularity of this data is relatively coarse for construction units. However, from the perspective of complete functionality, it sometimes mixes civil engineering and equipment together. But from the perspective of cost collection, civil engineering, equipment procurement, and equipment installation should be clearly separated. Therefore, it is not appropriate to directly use the quality-based structure as the cost collection list.

[0037] During measurement and settlement, the quantity of work settled in each period is first based on the quality units that have passed acceptance for measurement and approval. Then, after the approval of the visa forms for all quality units that can be settled in the current period, the quantity data is summarized according to the items in the contract bill of quantities, and the settlement approval process is executed.

[0038] Based on the above description, it can be seen that when collecting costs, if the cost is collected based on any of the above units, problems such as the data granularity not being able to cover all data, the data granularity being too coarse or too fine will occur, which will lead to uncontrollable problems in the actual cost collection.

[0039] However, research on the above business data revealed that the division of these various units is actually centered around the final delivered building structure. For example, the preliminary estimate is the cost for each building; the contract quantity is designed for the construction quantity of the building to be delivered under the contract; the construction drawing design is for a certain structure or equipment inside the building; the construction unit division is for completing the construction of a certain building structure; the quality unit division is for the acceptance of a certain structure or equipment in the building that has complete functions; and the project is used as the first level of data in the PBS list to achieve cost aggregation when multiple projects are running concurrently.

[0040] The main building list data, such as photovoltaic arrays, substations, monitoring stations, transmission lines, access roads, etc., are obtained from the main building list of the preliminary design results. This data is used as the second-level data in the PBS list for the cost collection of building groups with single functions in the project.

[0041] The third-level data of the PBS inventory is obtained from the overall layout drawings of each building complex. For example, photovoltaic array inventory data is obtained from the overall layout drawing of the photovoltaic array, transmission tower data is obtained from the overall layout drawing of the transmission line, and the main civil structure data of the substation and control station are obtained from the overall layout drawing of the substation and control station. The third-level data is used for cost collection of individual buildings with a single function in the project.

[0042] Obtain the fourth-level data of the PBS list from the preliminary estimate list. As mentioned above, the lowest-level node data in the preliminary estimate cannot be selected because its granularity is too fine and unsuitable for cost aggregation items. We can select the second-to-last or third-to-last level in the preliminary estimate data as the fourth-level data of the PBS list, used to aggregate the costs of a complete civil structure or set of equipment in a single building. For the main project of a photovoltaic power station, for example, we can select the data at the level of photovoltaic array equipment, civil pile foundation, array support, booster station equipment, booster station civil structure, control station equipment, and control station civil structure from the preliminary estimate data as the fourth level of the PBS list. The fourth-level PBS list is also the lowest-level cost aggregation item planned in this invention.

[0043] By constructing the PBS list above, we can obtain a four-level PBS list at the start of the project: project - building complex - individual building - complete equipment / civil structure within the individual building. The lowest level list items are slightly more detailed than individual buildings, but coarser in granularity than quality units, construction units, etc., which is conducive to the collection of relevant data and supporting materials.

[0044] Step 2: Establish the relationship between the cost collection list and various business data. After the cost collection list is established, before automatic collection is executed, it is necessary to establish the relationship between various business data and cost units. This includes the relationship with the budget item, the relationship with the contract quantity, the relationship with the construction drawings, the relationship with the construction unit and its detailed design, and the relationship with the quality unit. For example:

[0045] Association between budget and cost unit: Since the cost collection items of Level 4 PBS are data obtained from the budget hierarchy code, they have a natural relationship and can be automatically associated with the budget items directly based on the code or name of the cost collection items.

[0046] Relationship with Construction Design: Construction drawings and quantities are specific to building structures. Levels 2 and 3 of the PBS correspond to building complexes and individual buildings, while Level 4 corresponds to the building structure or equipment within an individual building. Automatic matching and association can be achieved based on the corresponding building structure identified on the construction drawings, following the rules of the building structure name or number. Furthermore, construction drawings themselves have varying granularities (coarse (overall, general layout, etc.) and fine (detailed drawings for each design specialty). Therefore, when matching construction drawings with cost collection items, it is not limited to Level 4; it can flexibly correspond to Levels 2, 3, and 4 based on the granularity of the building structure represented by the construction drawings.

[0047] The relationship between the contract quantities and cost units for each section: The contract quantities come from the tender design, which is based on the budget estimate. This relationship can be used to connect the tender quantities and the budget estimate. That is, by using the source budget estimate item of the contract quantity item in the tender design, we can jump to the link between the budget estimate item and the PBS cost collection list.

[0048] The relationship between construction units, quality units and cost units: Construction units and quality units are generally divided by the supervision unit, the construction unit and the contracting unit based on design results, industry standards or enterprise templates, etc., which has a relatively obvious human factor and is generally fine-grained. They are generally divided into a hierarchical structure of section - single building - sub-project - sub-item project - unit project.

[0049] Taking the construction of photovoltaic array #1 as an example, a typical unit project can be the first row of photovoltaic power generation modules of photovoltaic array #1; the sub-projects above it are equipment installation projects; the sub-projects above it are complete sets of power generation equipment; and the single building above it is photovoltaic array #1.

[0050] The linking of this data to the PBS cost collection list can be performed at the sub-project level. Based on the sub-project information and the individual building it belongs to, a similarity-based comparison method is used in the PBS structure list. The comparison is performed between the individual building / sub-project levels and the PBS levels 3 and 4, and the data with the highest similarity is automatically linked. After automatic linking, some manual verification and adjustment are required, but this significantly reduces the workload compared to the traditional manual comparison method.

[0051] Step 3: The investment costs are automatically aggregated under the cost collection items to obtain an automatically aggregated list. These aggregations, building upon steps 1 and 2, can all be automated, eliminating the workload of manual aggregation in the traditional model. For example:

[0052] Budget cost aggregation: By utilizing the relationship between the preliminary budget items and the expense aggregation items, the amount of the preliminary budget items attached to the 4th level PBS expense aggregation items can be automatically calculated. Then, the budget cost aggregation of the 1st, 2nd and 3rd level PBS expense aggregation items is completed by recursively going up level by level.

[0053] Accumulation of committed costs: Committed costs in engineering refer to the amount of the signed contract. Similar to the accumulation of budget costs, by leveraging the relationship between the contract bill of quantities items and the cost accumulation items, the contract bill of quantities items linked to the cost accumulation items of the 4th level PBS are automatically calculated. Then, the committed costs of the cost accumulation items of the 1st, 2nd and 3rd level PBS are completed in a recursive manner.

[0054] Output value and inspection / evaluation, measurement data collection: Output value refers to the quantity of completed and accepted work. By utilizing the relationship between PBS cost collection items and quality classification, the detailed work quantity data, inspection / evaluation data, and measurement / evaluation data of the quality unit's visa sheet can be automatically collected into the associated PBS cost collection items. Then, by using a hierarchical upward recursive method, the output value collection of all PBS cost collection items can be completed.

[0055] Collection of actual costs: Actual costs come from contract settlement, which is based on the contract quantity. Therefore, similar to committed costs, the settlement amount of the contract quantity items linked to the cost collection items can be automatically calculated by leveraging the relationship between the contract quantity list items and the cost collection items. Then, the actual costs of the cost collection items of the PBS at the 4th level can be collected by recursively going up the hierarchy.

[0056] Collection of construction drawings and on-site construction data: By leveraging the link between construction drawings and PBS cost collection items, the construction drawings and design quantities are collected in the PBS cost collection items. On-site construction data, such as the personnel, materials, and machinery invested, the daily construction volume, on-site construction problems and related measures, and on-site photos, are generally based on the construction logs registered by the construction units. By relying on the link between the construction units and PBS cost collection items, these construction data can be collected. Design drawings and design quantities, on-site construction data, quality inspection and evaluation data, and measurement and certification data all serve as supporting materials for completing the output value and actual costs in the PBS cost collection items.

[0057] Step 4: Perform quality verification on the target items in the automatically collected list from Step 3, and summarize the obtained quality verification results to obtain a quality verification list. Step 5: Match each quality verification item in the quality verification list with the preset construction acceptance strategy form and execute the corresponding preset construction acceptance strategy. Acceptance Failure Strategy: If a quality verification item does not meet the preset construction acceptance standards, i.e., it does not meet the expected quality requirements, the acceptance failure strategy is executed. For failed items, corresponding measures need to be taken for rectification or repair to meet the acceptance standards. Rectification Measures: For failed quality verification items, specific rectification plans and measures need to be formulated to ensure that the problems are resolved and repaired in a timely manner. Relevant responsible persons or teams can be assigned to be responsible for the rectification work, and the rectification tasks should be completed within the specified time. Re-verification: After rectification, the relevant items need to be re-verified to ensure that the problems are effectively resolved and the quality is guaranteed. If the re-verification results meet the acceptance standards, the acceptance pass strategy is executed; otherwise, rectification and verification continue until the acceptance requirements are met. Through the execution of the above strategies, the quality of the project can be effectively ensured to meet the standards, and quality problems can be identified and resolved in a timely manner, ensuring the smooth progress and final delivery of the project.

[0058] Step 1: Establish standard rules for classifying expense items and determine that the expense collection list refers to:

[0059] The initial minimum aggregation granularity of each business item in the main project of this photovoltaic power station construction period is collected separately. A standard aggregation granularity is established for the main project of this photovoltaic power station construction period. If the initial minimum aggregation granularity of the target business item is lower than the standard aggregation granularity, the standard aggregation granularity is set as the latest minimum aggregation granularity of the target business item. If the initial minimum aggregation granularity of the target business item is greater than or equal to the standard aggregation granularity, the initial minimum aggregation granularity of the target business item is set as the latest minimum aggregation granularity of the target business item. Then, each business item is divided into aggregation levels to obtain multiple cost aggregation items. According to the division results, a corresponding tag set is preset for each cost aggregation at each level. Then, all tag sets are summarized and a cost aggregation list is established according to the aggregation level division relationship of their respective businesses.

[0060] In step two, establishing the relationship between the cost collection list and various business data refers to: after the cost collection list is established, establishing the relationship between various business data and cost units, including the relationship with the budget item, the relationship with the contract quantity, the relationship with the construction drawings, the relationship with the construction unit and its detailed design, and the relationship with the quality unit.

[0061] In step three, the execution investment cost refers to:

[0062] The collection of investment costs for the main project during the construction period of a photovoltaic power station includes:

[0063] Collection of various costs: estimated cost collection, committed cost collection, output value collection, and actual expense collection;

[0064] Collection of various cost support data: collection of design data, collection of construction data, collection of quality data, and collection of measurement data.

[0065] In step three, the collection of investment costs for the main construction project during the photovoltaic power station construction period follows the following logic:

[0066] Retrieve the set of all tags for the collection target in the cost collection list;

[0067] The aggregation similarity between two adjacent aggregation granularities is then filtered sequentially, starting with the largest aggregation granularity and ending with the smallest aggregation granularity.

[0068] The tag sets of two adjacent tag sets at a higher tag set level are defined as the master set, and the tag sets at a lower tag set level are defined as the slave sets. The master set is compared with multiple slave sets using a similarity calculation method to obtain the similarity values ​​between the master set and multiple slave sets. These similarity values ​​are then compared with a preset similarity threshold. Slave sets with similarity values ​​greater than or equal to the similarity threshold are retained, while the remaining slave sets are removed. All the retained slave sets and the master set constitute a membership group at the tag set level of the master set. For example, in the PBS structure list, multiple Level 4 PBS cost tag sets and their common Level 3 PBS cost tag sets constitute a membership group.

[0069] By summarizing all the subordinate groups, an automatic target aggregation list is obtained.

[0070] The process of calculating similarity between the main set and multiple subordinate sets, and obtaining the similarity values ​​between the main set and each of the subordinate sets, refers to:

[0071] Obtain similar label data from the label set of the main set and use it as the first vector. Obtain similar label data from the label sets of multiple secondary sets and use it as the second vector. Calculate the cosine similarity between the first vector and the multiple second vectors respectively.

[0072] In step four, the quality verification of the target collection items in the automatically collected list from step three refers to:

[0073] For each membership group, quality verification is performed. The verification logic is as follows: obtain the cost data of all slave sets in the membership group and label them as CFi; obtain the preset cost coefficient FXi corresponding to the cost data CFi of all slave sets; and obtain the standard cost data corresponding to the cost data CFi of all slave sets and label them as BFi. Then, calculate the quality verification value of the membership group. ZLi is the quality verification value of the subordinate relationship group. Then, the quality verification value ZLi of the subordinate relationship group is compared with the preset verification threshold. If the quality verification value ZLi of the subordinate relationship group is less than or equal to the preset verification threshold, the subordinate relationship group passes the acceptance test. If the quality verification value ZLi of the subordinate relationship group is greater than the preset verification threshold, the subordinate relationship group fails the acceptance test.

[0074] Example 2

[0075] To effectively manage and monitor investment costs during the construction of photovoltaic power plants, and to ensure the effective use of investment and the smooth implementation of projects, this invention proposes a method for collecting investment costs of the main engineering works during the construction period of photovoltaic power plants, comprising the following steps:

[0076] Step 1: Establish standard rules for classifying cost items and determine the cost collection list. In this step, clear standards and rules need to be developed to classify different cost items. These rules can be formulated based on the specific circumstances and requirements of the photovoltaic power station construction. The cost collection list needs to cover all major investment cost items, such as land acquisition costs, construction costs, equipment procurement costs, design fees, and supervision fees. Developing this list makes the cost collection work more standardized and orderly. In this invention, it refers to: collecting the initial minimum collection granularity of each business item in the main project of this photovoltaic power station construction period, and establishing unified standards for the main project of this photovoltaic power station construction period. The standard aggregation granularity is determined by the following: if the initial minimum aggregation granularity of the target item is lower than the standard aggregation granularity, the standard aggregation granularity is set to the latest minimum aggregation granularity of the target item; if the initial minimum aggregation granularity of the target item is greater than or equal to the standard aggregation granularity, the initial minimum aggregation granularity of the target item is set to the latest minimum aggregation granularity of the target item. Then, each item is divided into aggregation levels to obtain multiple cost aggregation items. Based on the division results, a corresponding tag set is preset for each cost aggregation at each level. Then, all tag sets are summarized and a cost aggregation list is established according to the aggregation level division relationship of their respective items.

[0077] Step Two: Establish the correlation between the cost collection list and various business data. In this step, it is necessary to establish the correlation between the cost collection list and actual business data so that various business data can be mapped and collected with the corresponding cost collection items. This business data can include budget data, contract data, construction progress data, quality acceptance data, etc. Establishing the correlation between the list and business data can automate and intelligentize the cost collection process. In this invention, this refers to: after the cost collection list is established, establishing the correlation between various business data and cost units, including correlation with budget items, correlation with contract quantities, correlation with construction drawings, correlation with construction units and their detailed designs, and correlation with quality units.

[0078] Step 3: Automatically aggregate investment costs into the cost aggregation items to obtain an automatic aggregation list. In this step, an automated system or software tool aggregates investment costs according to pre-determined rules and lists. This can be achieved by processing and analyzing various business data to automatically allocate relevant costs to the corresponding aggregation items. Automatic aggregation improves the efficiency and accuracy of cost aggregation. In this invention, the aggregation of investment costs for the main project during the construction period of a photovoltaic power station includes:

[0079] Collection of various costs: estimated cost collection, committed cost collection, output value collection, and actual expense collection;

[0080] Collection of various cost support data: collection of design data, collection of construction data, collection of quality data, and collection of measurement data.

[0081] The following logic is followed when collecting investment costs for the main construction phase of a photovoltaic power station:

[0082] Retrieve the set of all tags for the collection target in the cost collection list;

[0083] The aggregation similarity between two adjacent aggregation granularities is then filtered sequentially, starting with the largest aggregation granularity and ending with the smallest aggregation granularity.

[0084] The tag sets of two adjacent tag sets at a higher tag set level are defined as the main set, and the tag sets at a lower tag set level are defined as the secondary sets. The main set is compared with multiple secondary sets using similarity calculation methods to obtain similarity values. These similarity values ​​are then compared with a preset similarity threshold. Secondary sets with similarity values ​​greater than or equal to the threshold are retained, while the rest are discarded. Similar tag data from the main set's tag set is used as the first vector, and similar tag data from the multiple secondary sets' tag sets is used as the second vector. The cosine similarity between the first vector and the multiple second vectors is calculated. All retained secondary sets and the main set constitute a membership group for the tag set's tag set level. The tag set includes a hierarchy tag for specifying the tag set level, a business tag for specifying the business to which it belongs, a similarity tag for similarity calculation, and a split tag for distinguishing between actual data and preset planning data. All membership groups are summarized to obtain the target automatic tag set list.

[0085] Step 4: Perform quality verification on the target items in the automatically collected list, and summarize the quality verification results to obtain a quality verification list. In this step, the automatically collected list needs to be quality verified. This can be achieved by comparing and verifying it with actual business data. The verification results can be categorized and summarized according to quality standards to obtain a quality verification list. In this invention, this refers to: performing quality verification for each membership group. The verification logic is as follows: obtain the cost data of all sub-sets in the membership group and label them as CFi; obtain the preset cost coefficient FXi corresponding to the cost data CFi of all sub-sets; and obtain the standard cost data corresponding to the cost data CFi of all sub-sets and label them as BFi. Then, calculate the quality verification value for the membership group. ZLi is the quality verification value of the subordinate relationship group. Then, the quality verification value ZLi of the subordinate relationship group is compared with the preset verification threshold. If the quality verification value ZLi of the subordinate relationship group is less than or equal to the preset verification threshold, the subordinate relationship group passes the acceptance test, which means that all items corresponding to the subordinate sets in the subordinate relationship group can be accepted. If the quality verification value ZLi of the subordinate relationship group is greater than the preset verification threshold, the subordinate relationship group fails the acceptance test, which means that all items corresponding to the subordinate sets in the subordinate relationship group cannot be accepted together. This is because all the subordinate sets in the subordinate relationship group correspond to a whole that can be accepted as a whole. Moreover, in this way, the quality verification of each target subordinate relationship group can be performed to determine whether it can be accepted as a whole.

[0086] Step 5: Match each quality verification item in the quality verification checklist with the pre-set construction acceptance strategy form and execute the corresponding pre-set construction acceptance strategy; finally, based on the results in the quality verification checklist, process and decide on each quality verification accordingly. This may involve adjusting and correcting abnormal data, as well as adhering to and implementing acceptance standards. Process the quality verification results according to the pre-set construction acceptance strategy to ensure that investment costs during the photovoltaic power station construction process are effectively managed and controlled.

[0087] In summary, by following the steps above, a complete method for collecting investment costs for the main construction phase of a photovoltaic power station can be established, enabling standardized management and effective monitoring of investment costs, and ensuring the smooth implementation of the project and the effective utilization of investment.

[0088] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0089] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0090] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer 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 implementation should not be considered beyond the scope of this application.

[0091] 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.

[0092] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for collecting investment costs of the main project during the construction period of a photovoltaic power station, characterized in that, Includes the following steps: Step 1: Establish standard rules for classifying expense items and determine the expense collection list; Step 2: Establish the relationship between the expense collection list and various business data; Step 3: Automatically aggregate investment costs under the cost aggregation item to obtain an automatic aggregation list; Step 4: Perform quality verification on the target collection items in the automatically collected list in Step 3, and summarize the quality verification results to obtain a quality verification list; Step 5: Match each quality verification item in the quality verification checklist with the preset construction acceptance strategy form and execute the corresponding preset construction acceptance strategy.

2. The method for collecting investment costs of the main project during the construction period of a photovoltaic power station according to claim 1, characterized in that, Step 1: Establish standard rules for classifying expense items and determine that the expense collection list refers to: The initial minimum aggregation granularity of each business item in the main project of this photovoltaic power station construction period is collected separately. A standard aggregation granularity is established for the main project of this photovoltaic power station construction period. If the initial minimum aggregation granularity of the target business item is lower than the standard aggregation granularity, the standard aggregation granularity is set as the latest minimum aggregation granularity of the target business item. If the initial minimum aggregation granularity of the target business item is greater than or equal to the standard aggregation granularity, the initial minimum aggregation granularity of the target business item is set as the latest minimum aggregation granularity of the target business item. Then, each business item is divided into aggregation levels to obtain multiple cost aggregation items. According to the division results, a corresponding tag set is preset for each cost aggregation at each level. Then, all tag sets are summarized and a cost aggregation list is established according to the aggregation level division relationship of their respective businesses.

3. The method for collecting investment costs of the main project during the construction period of a photovoltaic power station according to claim 2, characterized in that, In step two, establishing the relationship between the cost collection list and various business data refers to: after the cost collection list is established, establishing the relationship between various business data and cost units, including the relationship with the budget item, the relationship with the contract quantity, the relationship with the construction drawings, the relationship with the construction unit and its detailed design, and the relationship with the quality unit.

4. The method for collecting investment costs of the main project during the construction period of a photovoltaic power station according to claim 3, characterized in that, In step three, the execution investment cost refers to: The collection of investment costs for the main project during the construction period of a photovoltaic power station includes: Collection of various costs: estimated cost collection, committed cost collection, output value collection, and actual expense collection; Collection of various cost support data: collection of design data, collection of construction data, collection of quality data, and collection of measurement data.

5. The method for collecting investment costs of the main project during the construction period of a photovoltaic power station according to claim 4, characterized in that, In step three, the collection of investment costs for the main construction project during the photovoltaic power station construction period follows the following logic: Retrieve the set of all tags for the collection target in the cost collection list; The aggregation similarity between two adjacent aggregation granularities is then filtered sequentially, starting with the largest aggregation granularity and ending with the smallest aggregation granularity. The tag set of two adjacent tag sets at a higher tag set level is defined as the main set, and the tag set at a lower tag set level is defined as the secondary set. The main set is compared with multiple secondary sets using a similarity calculation method to obtain the similarity values ​​between the main set and multiple secondary sets. Then, these similarity values ​​are compared with a preset similarity threshold. The secondary sets corresponding to similarity values ​​greater than or equal to the similarity threshold are retained, and the remaining secondary sets are removed. All the retained secondary sets and the main set constitute a membership group of the tag set at the tag set level of the main set. By summarizing all the subordinate groups, an automatic target aggregation list is obtained.

6. The method for collecting investment costs of the main project during the construction period of a photovoltaic power station according to claim 5, characterized in that, The process of calculating similarity between the main set and multiple subordinate sets, and obtaining the similarity values ​​between the main set and each of the subordinate sets, refers to: Obtain similar label data from the label set of the main set and use it as the first vector. Obtain similar label data from the label sets of multiple secondary sets and use it as the second vector. Calculate the cosine similarity between the first vector and the multiple second vectors respectively.

7. The method for collecting investment costs of the main project during the construction period of a photovoltaic power station according to claim 6, characterized in that, In step four, the quality verification of the target collection items in the automatically collected list from step three refers to: For each membership group, quality verification is performed. The verification logic is as follows: obtain the cost data of all slave sets in the membership group and label them as CFi; obtain the preset cost coefficient FXi corresponding to the cost data CFi of all slave sets; and obtain the standard cost data corresponding to the cost data CFi of all slave sets and label them as BFi. Then, calculate the quality verification value of the membership group. ZLi is the quality verification value of the subordinate relationship group. Then, the quality verification value ZLi of the subordinate relationship group is compared with the preset verification threshold. If the quality verification value ZLi of the subordinate relationship group is less than or equal to the preset verification threshold, the subordinate relationship group passes the acceptance test. If the quality verification value ZLi of the subordinate relationship group is greater than the preset verification threshold, the subordinate relationship group fails the acceptance test.

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