Bus parameter determination method, device, equipment, storage medium and product

Abstract

The application discloses a bus parameter determination method, device, equipment, storage medium and product, relates to the electric digital data processing technical field, and the disclosed bus parameter determination method comprises the following steps: acquiring the working condition parameters of a historical project corresponding to the equipment type of the required electrical equipment in a target process according to the equipment type; estimating the working condition parameters of the target process according to the working condition parameters of the historical project; correcting the total installed power of the target process based on the working condition parameters of the target process to obtain a target total installed power; and determining the bus parameters adapted to the target process based on the target total installed power, effectively avoiding the problem of excessively high bus parameters and improving the reliability of the power system.

Description

Technical Field

[0001] This application relates to the field of electrical digital data processing technology, and in particular to methods, apparatus, equipment, storage media and products for determining bus parameters. Background Technology

[0002] In the field of industrial power distribution technology, busbars, as key conductive components in substations and power distribution equipment, undertake the core functions of power collection, distribution, and transmission. Therefore, the rationality of busbar selection directly affects the safety and economy of the power system. Traditional busbar selection methods typically determine busbar parameters based on rated installed capacity. This method can lead to a mismatch between the determined busbar parameters and actual operating conditions, making it difficult to meet the reliability requirements of the power system. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, equipment, storage medium, and product for determining bus parameters, aiming to solve the technical problem that the bus parameters determined by traditional bus selection methods do not match the actual operating conditions and are difficult to meet the reliability requirements of power systems.

[0004] To achieve the above objectives, this application proposes a method for determining bus parameters. The method includes: obtaining the operating condition parameters of historical projects corresponding to the equipment type of the electrical equipment required in the target process; estimating the operating condition parameters of the target process based on the operating condition parameters of the historical projects; correcting the total installed power of the target process based on the operating condition parameters of the target process to obtain the target total installed power; and determining the bus parameters adapted to the target process based on the target total installed power.

[0005] In this embodiment, based on the equipment type of the electrical equipment required in the target process, the operating condition parameters of historical projects for the corresponding equipment type are obtained; based on the operating condition parameters of the historical projects, the operating condition parameters of the target process are estimated; and based on the operating condition parameters of the target process, the total installed power of the target process is corrected. Since different equipment types have different electrical characteristics, the operating condition parameters of historical projects provide electrical references for different equipment, ensuring the accuracy of the operating condition parameters of the target process. On this basis, the total installed power of the target process is corrected based on the operating condition parameters of the target process. The corrected total installed power is closer to the actual operating conditions of the target process, breaking the limitations of traditional one-size-fits-all selection based on rated installed power, effectively avoiding the problem of excessively high bus parameters, and thus improving the reliability of the power system.

[0006] In one embodiment, when there are multiple historical projects, there are multiple operating parameters for each historical project. Estimating the operating parameters of the target process based on the operating parameters of the historical projects includes: determining the dispersion and central tendency of the operating parameters of the multiple historical projects; and obtaining the operating parameters of the target process from the operating parameters of the multiple historical projects based on the dispersion and central tendency of the operating parameters of the multiple historical projects.

[0007] In this embodiment, the operating parameters of the target process are obtained from the operating parameters of multiple historical projects based on their dispersion and central tendency. Dispersion reflects the magnitude of the difference in the same electrical parameter value across different historical projects, while central tendency reflects the average level or common value of a certain operating parameter across multiple historical projects. By analyzing dispersion and central tendency, the distribution characteristics of the data can be more comprehensively understood, enabling more accurate acquisition of the operating parameters of the target process from numerous historical projects.

[0008] In one embodiment, the operating parameters of historical projects include historical total utilization coefficients, and the operating parameters of the target process include standard total utilization coefficients. Obtaining the operating parameters of the target process from the operating parameters of multiple historical projects, based on the dispersion and central tendency of the operating parameters of multiple historical projects, includes: constructing a first normal distribution model based on the dispersion and central tendency of multiple historical total utilization coefficients; obtaining the target historical total utilization coefficient corresponding to the cumulative probability set in the first normal distribution model; and using the target historical total utilization coefficient as the standard total utilization coefficient of the target process.

[0009] In this embodiment, the standard total utilization coefficient of the target process is obtained from the historical total utilization coefficients of multiple historical projects based on their dispersion and central tendency. Dispersion reflects the magnitude of differences in the same historical total utilization coefficient across different historical projects, while central tendency reflects the average level or common value of a certain historical total utilization coefficient across multiple historical projects. By analyzing dispersion and central tendency, the distribution characteristics of the data can be more comprehensively understood, and the standard total utilization coefficient of the target process can be more accurately obtained from the historical total utilization coefficients of numerous historical projects.

[0010] In one embodiment, the operating condition parameters of historical projects include the effective number of historical electrical equipment units, and the operating condition parameters of the target process include the effective number of standard electrical equipment units. Obtaining the operating condition parameters of the target process from the operating condition parameters of multiple historical projects, based on the dispersion and central tendency of the operating condition parameters of multiple historical projects, includes: constructing a second normal distribution model based on the dispersion and central tendency of the effective number of historical electrical equipment units; obtaining the target effective number of historical electrical equipment units corresponding to the cumulative probability set in the second normal distribution model; and using the target effective number of historical electrical equipment units as the effective number of standard electrical equipment units for the target process.

[0011] In this embodiment, the standard effective number of electrical equipment for the target process is obtained from the effective number of historical electrical equipment in multiple historical projects by considering the dispersion and central tendency of the effective number of historical electrical equipment in those projects. The dispersion reflects the difference in the effective number of the same historical electrical equipment across different historical projects, while the central tendency reflects the average level or common value of a certain historical electrical equipment's effective number across multiple historical projects. By analyzing the dispersion and central tendency, the distribution characteristics of the data can be more comprehensively understood, enabling a more accurate extraction of the standard effective number of electrical equipment for the target process from the effective number of historical electrical equipment in numerous historical projects.

[0012] In one embodiment, the operating parameters of historical projects include historical total installed power, and the operating parameters of the target process include standard historical total installed power. Based on the operating parameters of historical projects, the estimated operating parameters of the target process include: selecting the largest historical total installed power from the historical total installed power of multiple historical projects as the standard historical total installed power.

[0013] In this embodiment of the application, by using the maximum historical total installed capacity among multiple historical projects as the standard historical total installed capacity, it is possible to ensure that the power system still has sufficient power reserves when facing peak loads, avoiding problems such as system collapse and equipment damage caused by insufficient power, and ensuring the stability and continuity of power system operation.

[0014] In one embodiment, correcting the total installed power of the target process based on the operating parameters of the target process to obtain the target total installed power includes: calculating a comprehensive correction coefficient for the total installed power of the target process based on the operating parameters of the target process, wherein the operating parameters of the target process include the standard total utilization factor, the effective number of standard electrical equipment, and the standard historical total installed power; and correcting the total installed power of the target process using the comprehensive correction coefficient to obtain the target total installed power.

[0015] In this embodiment of the application, by calculating the comprehensive correction coefficient and using the comprehensive correction coefficient to correct the total installed power of the target process, it is possible not only to accurately reflect the actual power demand of the equipment during operation, but also to reasonably assess the overall impact of the equipment on the total installed power, making the target total installed power more consistent with the actual working conditions and more accurate.

[0016] In one embodiment, calculating the comprehensive correction factor for the total installed power of the target process based on the operating parameters of the target process includes: obtaining the maximum coefficient associated with the standard total utilization factor and the effective number of standard electrical equipment; calculating the comprehensive total load factor based on the maximum coefficient and the standard total utilization factor; calculating the installation deviation correction factor based on the standard historical total installed power, the standard total utilization factor, the total installed power of the target process, and the comprehensive total load factor; and correcting the comprehensive total load factor using the installation deviation correction factor to obtain the comprehensive correction factor.

[0017] In this embodiment, a calibration step is introduced. Based on the standard historical total installed power, standard total utilization factor, target process total installed power, and comprehensive total load factor, an installation deviation correction factor is calculated. This installation deviation correction factor is then used to correct the comprehensive total load factor, resulting in a comprehensive correction factor, thus improving the accuracy of the comprehensive correction factor.

[0018] In one embodiment, determining the bus parameters adapted to the target process based on the target total installed power includes: calculating the bus current required for the target process based on the target total installed power; and determining the bus parameters adapted to the target process based on the bus current.

[0019] In this embodiment, the bus current required for the target process is calculated by correcting the target total installed power, and then the bus parameters suitable for the target process are determined based on the bus current, thereby improving the accuracy of bus selection.

[0020] In one embodiment, determining the bus parameters adapted to the target process based on the bus current includes:

[0021] Based on the relationship table between bus current, preset bus current and preset bus parameters, determine the bus parameters that are compatible with the target process.

[0022] In this embodiment, the final busbar parameters are determined by querying a preset relationship table, thereby connecting the calculated current value with the standard busbar specifications in engineering practice. This completes the final step from theoretical calculation to physical selection, ensuring the feasibility and standardization of the solution.

[0023] Furthermore, to achieve the above objectives, this application also proposes a busbar parameter determination device, comprising: an acquisition module, used to acquire the operating condition parameters of historical projects corresponding to the equipment type of the electrical equipment required in the target process; a processing module, used to estimate the operating condition parameters of the target process based on the operating condition parameters of the historical projects; to correct the total installed power of the target process based on the operating condition parameters of the target process to obtain the target total installed power; and to determine the busbar parameters adapted to the target process based on the target total installed power.

[0024] In addition, to achieve the above objectives, this application also proposes a bus parameter determination device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the bus parameter determination method as described above.

[0025] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the bus parameter determination method described above.

[0026] In addition, to achieve the above objectives, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the bus parameter determination method as described above. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0028] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart illustrating an embodiment of the busbar parameter determination method provided in this application;

[0030] Figure 2 This is a detailed flowchart of step S20 of the busbar parameter determination method provided in this application;

[0031] Figure 3 This is a detailed flowchart of step S22 of the method for determining bus parameters provided in this application;

[0032] Figure 4 This is another detailed flowchart of step S22 of the bus parameter determination method provided in this application;

[0033] Figure 5 This is a detailed flowchart of step S30 of the busbar parameter determination method provided in this application;

[0034] Figure 6 A schematic diagram of the module structure of the bus parameter determination device provided in this application;

[0035] Figure 7 A schematic diagram of the device for determining busbar parameters provided in this application.

[0036] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0037] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0039] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0040] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0041] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0042] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0043] In the field of industrial power distribution technology, the stable and efficient operation of power systems is a core element ensuring the smooth operation of various industrial production activities. Substations and distribution equipment, as key hubs of the power system, undertake the important task of efficiently and reliably distributing electrical energy from the generation end to various electrical devices. Busbars, as the core conductive components in substations and distribution equipment, bear the critical functions of power collection, distribution, and transmission; their performance and the rationality of their selection directly affect the safety and economy of the entire power system.

[0044] Busbars are crucial components in power systems, connecting multiple electrical devices and enabling the centralized distribution of electrical energy. They collect power from upstream substations and then distribute it rationally to various distribution lines based on regional demand, ultimately delivering it to different loads. A busbar failure, such as a short circuit or overload, can paralyze the entire power system, causing widespread blackouts, significant economic losses, and potentially even safety accidents. Therefore, reliable busbar operation is fundamental to power system stability.

[0045] Traditional busbar selection methods primarily determine busbar parameters based on rated installed capacity. This approach provides a basic reference for busbar design to some extent; its core idea is to calculate busbar parameters, such as busbar specifications and capacity, based on the sum of the rated power of all electrical equipment in the system, combined with certain empirical coefficients. However, with the continuous development of industrial production and the increasing complexity of power systems, the limitations of this traditional selection method have gradually become apparent.

[0046] Busbar parameters determined based on rated installed capacity often fail to accurately reflect actual load conditions during operation. In actual industrial production, busbars selected according to rated installed capacity may experience excessively high or low load rates during operation. When the load rate is too high, the busbar operates under overload conditions for extended periods, accelerating its aging, increasing heat generation, reducing insulation performance, and even triggering short-circuit faults, severely impacting the reliability of the power system. Therefore, determining appropriate busbar parameters becomes crucial.

[0047] To address the aforementioned issues, this application proposes a method for determining bus parameters. The method includes: obtaining the operating condition parameters of historical projects corresponding to the equipment types of electrical equipment required in the target process; estimating the operating condition parameters of the target process based on the operating condition parameters of the historical projects; correcting the total installed power of the target process based on the operating condition parameters of the target process to obtain the target total installed power; and determining the bus parameters adapted to the target process based on the target total installed power.

[0048] In this embodiment, based on the equipment type of the electrical equipment required in the target process, the operating condition parameters of historical projects for the corresponding equipment type are obtained; based on the operating condition parameters of the historical projects, the operating condition parameters of the target process are estimated; and based on the operating condition parameters of the target process, the total installed power of the target process is corrected. Since different equipment types have different electrical characteristics, the operating condition parameters of historical projects provide electrical references for different equipment, ensuring the accuracy of the operating condition parameters of the target process. On this basis, the total installed power of the target process is corrected based on the operating condition parameters of the target process. The corrected total installed power is closer to the actual operating conditions of the target process, breaking the limitations of traditional one-size-fits-all selection based on rated installed power, effectively avoiding the problem of excessively high bus parameters, and thus improving the reliability of the power system.

[0049] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a desktop computer, tablet computer, personal computer, or mobile phone, or an electronic device or transformer parameter determination device capable of performing the above functions. The following description uses a transformer parameter determination device as an example to illustrate this embodiment and the subsequent embodiments.

[0050] Based on the above, this application provides a method for determining busbar parameters, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the busbar parameter determination method of this application.

[0051] In this embodiment, the method for determining bus parameters includes steps S10 to S40:

[0052] Step S10: Based on the equipment type of the electrical equipment required in the target process, obtain the operating condition parameters of the historical projects corresponding to the equipment type.

[0053] It should be noted that the design of the power system for a new energy plant involves different processes, each with its own unique characteristics, and therefore requires different busbar selection methods. The busbar parameter determination method proposed in this embodiment is applicable to processes within the battery manufacturing process.

[0054] For example, the target processes mentioned above could include battery stirring, cold pressing, die-cutting, assembly, and baking. The stirring process involves mixing the positive / negative electrode active materials, conductive agents, binders, and solvents to prepare a uniform electrode slurry. The cold pressing process involves pressing the coated electrode sheets at room temperature to increase material density, reduce thickness, and enhance conductivity. The die-cutting process involves precisely cutting the cold-pressed electrode sheets and separator to the battery dimensions to ensure assembly accuracy. The assembly process involves stacking / winding the positive electrode sheets, separator, and negative electrode sheets, and assembling them with the electrolyte and casing to form a battery pack / finished battery. The baking process involves baking the electrode sheets, separator, and casing at high temperatures to remove moisture and impurities, preventing internal gas generation and short circuits.

[0055] It should be noted that each target process has corresponding electrical equipment. For a specific target process, multiple electrical devices may be set up, each with a different type of equipment. The target process is executed by at least some of these multiple electrical devices, which can perform the same or different processing flows under that process; this application does not impose any restrictions on this.

[0056] For example, the equipment used in the mixing process can be electrode slurry mixing tanks, batching and conveying pumps, dispersers, etc. For the cold pressing process, the equipment can be electrode cold pressing machines, tension control roller motors, conveyor belt motors, etc. For the die-cutting process, the equipment can be electrode die-cutting machines, feeding motors, waste recycling motors, etc. For the assembly process, the equipment can be stacking / winding machines, electrolyte injection pumps, core packaging machines, etc. For the baking process, the equipment can be vacuum baking ovens, vacuum pumps, temperature circulating fans, etc.

[0057] Among them, historical projects refer to power distribution projects that have been implemented in the past and are of the same type as the target process, such as battery mixing processes that use similar electrical equipment. The operating parameters of historical projects are core data reflecting the power consumption characteristics of the equipment.

[0058] The operating parameters of historical projects are data from the actual operation of equipment in similar processes, rather than the theoretical rated values ​​on the equipment nameplate. For example, operating parameters of historical projects include, but are not limited to, historical total utilization factor, historical effective number of electrical equipment, and historical total installed power. These operating parameters accurately reflect the power consumption patterns of electrical equipment in actual production, providing a systematic basis for the parameter prediction of target processes, offering a reference benchmark for actual operating conditions, and making the prediction of operating parameters for target processes closer to reality.

[0059] In one alternative approach, an equipment database can be constructed based on the equipment types of electrical equipment used in mixing, cold pressing, die-cutting, assembly, and baking processes. This database also includes operating condition parameters for one or more historical projects related to each electrical equipment. Each historical project includes one or more electrical equipment. Thus, when a new project needs to be created, the equipment type of the target process in the new project is first determined by querying the equipment database. After determining the equipment types of the electrical equipment required in the target process, the operating condition parameters of the corresponding historical projects for that equipment type are obtained from the pre-constructed equipment database. Specifically, when determining the equipment type of the target process in the new project by querying the equipment database, the equipment name or power of each electrical device required for the target process can be obtained first. Based on this equipment name or power, the equipment type of each electrical device required in the target process is then retrieved from the equipment database.

[0060] Step S20: Estimate the operating parameters of the target process based on the operating parameters of historical projects.

[0061] The operating parameters of the target process are estimated based on the operating parameters of historical projects. For example, the operating parameters of the target process include, but are not limited to: standard total utilization factor, effective number of standard electrical equipment, and theoretical total installed power. These parameters reflect the actual operating status of the electrical equipment in the target process and are the core basis for subsequent power correction.

[0062] In one alternative approach, the operating parameters of historical projects can be input into a preset calculation model to estimate the operating parameters of the target process. For example, the calculation model can select reasonable operating parameters as the operating parameters of the target process based on the normal distribution of the operating parameters of historical projects. Alternatively, the preset calculation model can filter the operating parameters of historical projects, for example, by removing the minimum and maximum values, and then selecting the largest value from the remaining operating parameters as the operating parameters of the target process.

[0063] Step S30: Based on the operating parameters of the target process, correct the total installed power of the target process to obtain the target total installed power.

[0064] The total installed capacity refers to the maximum theoretical output capacity of the entire power system under ideal conditions. The total installed capacity of the target process is the sum of the rated power of all electrical equipment under the target process. If the rated power of each electrical equipment under the target process is the same, then the total installed capacity of the target process = the total number of equipment * the rated power of a single equipment.

[0065] The target total installed power is the value obtained by correcting the target process's total installed power using the operating parameters of the target process. This target total installed power is closer to the actual operating conditions of the target process.

[0066] In one alternative approach, the operating parameters of the determined target process can be input into a preset calculation model. The underlying calculation logic of this model then uses these operating parameters to correct the total installed power of the target process, resulting in the target total installed power. Because the total installed power of the target process can be corrected using its operating parameters, the corrected total installed power more closely approximates the actual operating conditions of the target process. This breaks away from the limitations of traditional one-size-fits-all selection based on rated installed power, effectively avoiding the problem of excessively high bus parameters, and thus improving the reliability of the power system.

[0067] Step S40: Based on the target total installed power, determine the bus parameters that are compatible with the target process.

[0068] The busbar parameters include, but are not limited to, the number of busbars, busbar capacity, busbar material, and busbar specifications, etc., and this application does not impose any restrictions on these parameters. The number of busbars required for each target process can be one or more.

[0069] In one alternative approach, a relationship table between the total installed power of each process and the bus parameters can be pre-established. In practical applications, the bus parameters suitable for the target process can be obtained by looking up the relationship table through the target total installed power.

[0070] In this embodiment, based on the equipment type of the electrical equipment required in the target process, the operating condition parameters of historical projects for the corresponding equipment type are obtained; based on the operating condition parameters of the historical projects, the operating condition parameters of the target process are estimated; and based on the operating condition parameters of the target process, the total installed power of the target process is corrected. Since different equipment types have different electrical characteristics, the operating condition parameters of historical projects provide electrical references for different equipment, ensuring the accuracy of the operating condition parameters of the target process. On this basis, the total installed power of the target process is corrected based on the operating condition parameters of the target process. The corrected total installed power is closer to the actual operating conditions of the target process, breaking the limitations of traditional one-size-fits-all selection based on rated installed power. By determining the bus parameters through the corrected target total installed power, the problem of excessively high bus parameters is effectively avoided, thereby improving the reliability of the power system.

[0071] In one feasible implementation, when there are multiple historical projects, there are multiple operating parameters for each historical project. (Refer to...) Figure 2 Step S20 above may include steps S21 to S22:

[0072] Step S21: Determine the dispersion and central tendency of the operating parameters of multiple historical projects.

[0073] Dispersion measures the degree to which a set of data deviates from its central value, reflecting the dispersion of the data. In operating parameters, it reflects the magnitude of differences in the same electrical parameter value across different historical projects. For example, the historical total utilization factor across various historical projects: a large dispersion indicates significant differences in the historical total utilization factor across different projects; a small dispersion indicates that the historical total utilization factor is relatively similar across projects. Common metrics for measuring dispersion include variance and standard deviation.

[0074] Central tendency refers to the tendency of a set of data to converge toward its central value, reflecting typical or representative values. For operating parameters, central tendency reflects the average level or common values ​​of a parameter across multiple historical projects. For example, the historical total utilization coefficient across various historical projects; central tendency indicates the approximate range of that coefficient in most projects. Commonly used metrics include mean, median, and mode.

[0075] In one alternative approach, operating condition parameter data from multiple historical projects can be collected, assuming there are n historical projects. The mean of these n historical projects is calculated; this mean reflects the central tendency of the operating condition parameters, i.e., the average level of the data. The variance of these n historical projects is also calculated; this variance reflects the degree of data dispersion. A larger variance indicates a greater deviation from the mean, and stronger dispersion. Calculating the mean allows for a quick understanding of the approximate levels of operating condition parameters across multiple historical projects, providing a basic reference for subsequent screening and comparison. Calculating the variance precisely quantifies the degree of data dispersion, helping to determine the magnitude of differences in operating condition parameters between different historical projects, thereby providing a more comprehensive understanding of the data distribution characteristics and offering a strong basis for accurately obtaining the operating condition parameters of the target process from numerous historical projects.

[0076] In another alternative approach, operating parameter data from multiple historical projects can be collected. First, the data is sorted. The median, or the average of the two middle values ​​after sorting the data from smallest to largest or largest to smallest, reflects the median level of the data, is unaffected by extreme values, and better reflects central tendency. The standard deviation is then calculated. The standard deviation is the square root of the variance, having the same dimension as the data, and more intuitively reflects the dispersion of the data. As a measure of central tendency, the median is more resistant to the interference of extreme values ​​than the mean, and can more accurately reflect the typical situation of operating parameters when outliers exist. The standard deviation presents the dispersion with the same dimension as the original data, making the understanding of data dispersion more intuitive and helping to more clearly grasp the fluctuation range of operating parameters across different historical projects, providing more reliable data characteristic information for subsequent steps.

[0077] Step S22: Based on the dispersion and central tendency of the working parameters of multiple historical projects, obtain the working parameters of the target process from the working parameters of multiple historical projects.

[0078] In one alternative approach, after calculating the dispersion and central tendency, a suitable threshold range can be set. For example, a range based on the standard deviation can be set, centered on the mean. By iterating through the operating parameters of multiple historical projects, parameters falling within this threshold range are selected. Projects corresponding to these parameters are more likely to have similar electrical characteristics to the target process, thus obtaining the operating parameters of the target process. By setting a threshold range based on dispersion and central tendency for filtering, projects with similar electrical characteristics to the target process can be quickly and effectively selected from a large number of historical projects, improving the accuracy and efficiency of obtaining the target process's operating parameters. This avoids the tedious process of manual analysis and, by utilizing the statistical characteristics of the data for filtering, makes the obtained parameters more representative and reliable.

[0079] In another alternative approach, operating parameters from multiple historical projects can be used as data points. Combined with the dispersion and central tendency information obtained above, a suitable clustering algorithm can be selected for cluster analysis to obtain the operating parameters of the target process. Specifically, taking the K-means clustering algorithm as an example, in K-means clustering, K central data points are first randomly selected, and then each data point is assigned to the cluster represented by the nearest central data point. Next, the central data point of each cluster is recalculated, and this process of assigning data points and recalculating central data points is repeated until the central data points no longer change or a preset number of iterations is reached. Based on the characteristics of the target process, the corresponding cluster is determined, and the operating parameters corresponding to the data points in this cluster are the obtained operating parameters of the target process. Cluster analysis can automatically group multiple historical projects based on the inherent characteristics of the data, grouping projects with similar electrical characteristics into the same cluster. Obtaining the operating parameters of the target process in this way can more comprehensively consider the similarities and differences between data, without being limited by subjectively set thresholds. It can discover potential classification patterns in the data, thereby more accurately obtaining operating parameters that match the target process, improving the accuracy and adaptability of parameter acquisition.

[0080] In this embodiment, the operating parameters of the target process are obtained from the operating parameters of multiple historical projects based on their dispersion and central tendency. Dispersion reflects the magnitude of the difference in the same electrical parameter value across different historical projects, while central tendency reflects the average level or common value of a certain operating parameter across multiple historical projects. By analyzing dispersion and central tendency, the distribution characteristics of the data can be more comprehensively understood, enabling more accurate acquisition of the operating parameters of the target process from numerous historical projects.

[0081] In one feasible implementation, the operating parameters of historical projects include the historical total utilization factor, and the operating parameters of the target process include the standard total utilization factor. When there are multiple historical projects, there will also be multiple historical total utilization factors. The historical total utilization factor is a comprehensive indicator measuring the utilization level of electrical equipment in historical projects; it can be obtained by dividing the sum of the average active power of each piece of electrical equipment in the historical projects by the sum of the total power of all equipment. The standard total utilization factor is determined based on the operating parameters of historical projects. Since each historical project has a corresponding historical total utilization factor, the standard total utilization factor here can be one of multiple historical total utilization factors.

[0082] Reference Figure 3 Step S22 above may include steps A221 to A223:

[0083] Step A221: Based on the dispersion and central tendency of multiple historical total utilization coefficients, construct the first normal distribution model.

[0084] The normal distribution, also known as the Gaussian distribution, is an important probability distribution. Its probability density function curve is bell-shaped, exhibiting symmetry, with the mean located on the axis of symmetry, and the curve gradually decreases towards both sides. The first normal distribution model here is constructed based on the dispersion (variance) and central tendency (mean) of multiple historical total utilization coefficients. It describes the probability distribution of historical total utilization coefficients, allowing us to understand the likelihood of different historical total utilization coefficients occurring.

[0085] In one alternative approach, using the mean as the central tendency and the variance as the dispersion, multiple historical total utilization coefficient data can be collected. First, the mean is calculated, reflecting the central tendency of the historical total utilization coefficients, i.e., the average level of the data. Then, the variance is calculated, reflecting the dispersion of the historical total utilization coefficients; the larger the variance, the more dispersed the data. Using the mean as the mean of a normal distribution and the standard deviation as the standard deviation of a normal distribution, a first normal distribution model is constructed.

[0086] Step A222: Obtain the target historical total utilization coefficient corresponding to the set cumulative probability from the first normal distribution model.

[0087] The cumulative probability of the historical total utilization coefficient represents the probability that the random variable takes a value less than or equal to a specific value. In the first normal distribution model, the cumulative probability corresponding to different historical total utilization coefficients can be calculated, reflecting the proportion of all possible cases where the historical total utilization coefficient does not exceed that specific value.

[0088] The set cumulative probability is a pre-determined cumulative probability value based on the actual working conditions and the characteristics of the target process. For example, this set cumulative probability can be set to 80%, meaning that when determining the standard total utilization coefficient of the target process, it may be desirable to find a target historical total utilization coefficient value such that the probability of all historical total utilization coefficients not exceeding this value is 80%. It should be noted that 80% can be used as a target threshold to determine the target historical total utilization coefficient. This indicates that this target historical total utilization coefficient is a relatively good but not extreme level among all historical total utilization coefficients, and has representative significance. It can be used to determine the standard total utilization coefficient of subsequent target processes, thereby improving the accuracy of the standard total utilization coefficient of the target process.

[0089] In one alternative approach, given a pre-constructed first normal distribution model, to query the target historical total utilization coefficient corresponding to a cumulative probability P, first transform the general normal distribution into a standard normal distribution. Based on the set cumulative probability P, look up the corresponding Z value in the standard normal distribution table. The cumulative probability corresponding to the set cumulative probability is then derived from Z.

[0090] Step A223: Use the target historical total utilization factor as the standard total utilization factor for the target process.

[0091] In this embodiment, the standard total utilization coefficient of the target process is obtained from the historical total utilization coefficients of multiple historical projects based on their dispersion and central tendency. Dispersion reflects the magnitude of differences in the same historical total utilization coefficient across different historical projects, while central tendency reflects the average level or common value of a certain historical total utilization coefficient across multiple historical projects. By analyzing dispersion and central tendency, the distribution characteristics of the data can be more comprehensively understood, and the standard total utilization coefficient of the target process can be more accurately obtained from the historical total utilization coefficients of numerous historical projects.

[0092] In one feasible implementation, the operating parameters of historical projects include the effective number of historical electrical equipment units, and the operating parameters of the target process include the effective number of standard electrical equipment units. When there are multiple historical projects, there are also multiple effective numbers of historical electrical equipment units. Specifically, if a group of actual electrical equipment units in a historical project has different power and operating modes, and is converted into a hypothetical group of electrical equipment units with identical power and operating modes, while maintaining its maximum calculated load, then the number of units in this hypothetical group is the effective number of units in this actual group, i.e., the effective number of historical electrical equipment units. This effective number of historical electrical equipment units can be obtained by the ratio of the square of the sum of the power consumption of each electrical equipment unit in the historical project to the sum of the squares of the power consumption of each electrical equipment unit in the historical project. The effective number of standard electrical equipment units is determined based on the effective number of historical electrical equipment units in the historical projects. Since each historical project has a corresponding effective number of historical electrical equipment units, the effective number of standard electrical equipment units here can be one of multiple effective numbers of historical electrical equipment units.

[0093] Reference Figure 4 The above step S22 may also include steps B221 to B223:

[0094] Step B221: Based on the dispersion and central tendency of the effective number of multiple historical electrical devices, construct a second normal distribution model.

[0095] The normal distribution, also known as the Gaussian distribution, is an important probability distribution. Its probability density function curve is bell-shaped, exhibiting symmetry, with the mean located on the axis of symmetry, and the curve gradually decreases towards both sides. The second normal distribution model here is constructed based on the dispersion (variance) and central tendency (mean) of the effective number of historical electrical devices. It describes the probability distribution of the effective number of historical electrical devices, allowing us to understand the likelihood of different effective numbers of historical electrical devices occurring.

[0096] In one alternative approach, using the mean as the central tendency and the variance as the dispersion, multiple historical total utilization factor data can be collected. First, the mean is calculated, reflecting the central tendency of the historical effective number of electrical devices, i.e., the average level of the data. Then, the variance is calculated, reflecting the dispersion of the historical effective number of electrical devices; the larger the variance, the more dispersed the data. Using the mean as the mean of a normal distribution and the standard deviation as the standard deviation of a normal distribution, a second normal distribution model is constructed.

[0097] Step B222: Obtain the effective number of target historical electrical devices with a cumulative probability corresponding to the set cumulative probability from the second normal distribution model.

[0098] In this context, the cumulative probability of the effective number of historical electrical devices represents the probability that the random variable takes a value less than or equal to a specific value. In the second normal distribution model, the cumulative probability corresponding to different effective numbers of historical electrical devices can be calculated, reflecting the proportion of all possible scenarios where the effective number of historical electrical devices does not exceed that specific value.

[0099] The set cumulative probability is a pre-determined cumulative probability value based on the actual working conditions and the characteristics of the target process. For example, this set cumulative probability can be set to 80%, meaning that when determining the effective number of standard electrical equipment units in the target process, it may be desirable to find a target historical effective number of electrical equipment units such that the probability of all historical effective numbers of electrical equipment units not exceeding this value is 80%. It should be noted that 80% can be used as a target threshold to determine the target historical effective number of electrical equipment units. This indicates that this target historical effective number of electrical equipment units is a better-than-average but not extreme level among all historical effective numbers of electrical equipment units, and has representative significance. It can be used to determine the effective number of standard electrical equipment units in subsequent target processes, thereby improving the accuracy of the effective number of standard electrical equipment units in the target process.

[0100] In one alternative approach, given a pre-constructed second normal distribution model, to query the effective number of target historical electrical devices corresponding to a cumulative probability P, the general normal distribution can first be transformed into a standard normal distribution. Based on the set cumulative probability P, the corresponding Z value is looked up in the standard normal distribution table. The effective number of target historical electrical devices corresponding to a cumulative probability equal to the set cumulative probability is then derived from the Z value.

[0101] Step B223: Use the target historical effective number of electrical equipment units as the standard effective number of electrical equipment units for the target process.

[0102] In this embodiment, the standard effective number of electrical equipment for the target process is obtained from the effective number of historical electrical equipment in multiple historical projects by considering the dispersion and central tendency of the effective number of historical electrical equipment in those projects. The dispersion reflects the difference in the effective number of the same historical electrical equipment across different historical projects, while the central tendency reflects the average level or common value of a certain historical electrical equipment's effective number across multiple historical projects. By analyzing the dispersion and central tendency, the distribution characteristics of the data can be more comprehensively understood, enabling a more accurate extraction of the standard effective number of electrical equipment for the target process from the effective number of historical electrical equipment in numerous historical projects.

[0103] In one feasible implementation, the operating parameters of historical projects include the historical total installed capacity, and the operating parameters of the target process include the standard historical total installed capacity. Since there are multiple historical projects, there are multiple historical total installed capacities. For a single historical project, there are multiple electrical devices, and each electrical device has a corresponding actual operating power. The actual operating power of each electrical device can be added together to obtain the historical total installed capacity corresponding to a single historical project. The historical total installed capacity corresponding to each historical project is known and can be directly obtained.

[0104] It should be noted that the standard historical total installed capacity of the target process is selected from the historical total installed capacity of multiple historical projects. The total installed capacity of the target process is the expected total installed capacity of the target process in the new project input by the user, and it differs from the historical total installed capacity.

[0105] Specifically, step S20 above includes step A21:

[0106] Step A21: Select the largest historical total installed capacity from the historical total installed capacity of multiple historical projects as the standard historical total installed capacity.

[0107] It should be noted that during project operation, instantaneous peak load situations may occur, such as the simultaneous startup of certain equipment in production. Selecting the maximum historical total installed capacity as the standard ensures that the power system still has sufficient power reserves when facing peak loads, avoiding problems such as system collapse and equipment damage due to insufficient power, and ensuring the stability and continuity of power system operation.

[0108] In this embodiment of the application, by using the maximum historical total installed capacity among multiple historical projects as the standard historical total installed capacity, it is possible to ensure that the power system still has sufficient power reserves when facing peak loads, avoiding problems such as system collapse and equipment damage caused by insufficient power, and ensuring the stability and continuity of power system operation.

[0109] In one feasible implementation, refer to Figure 5 Step S30 may include steps S31 to S32:

[0110] Step S31: Based on the operating parameters of the target process, calculate the comprehensive correction coefficient of the total installed power of the target process. The operating parameters of the target process include the standard total utilization factor, the effective number of standard electrical equipment, and the standard historical total installed power.

[0111] The comprehensive correction factor is a factor used to correct the total installed power of the target process, thereby improving the reliability of the total installed power of the target process.

[0112] It should be noted that equipment utilization varies significantly across different production processes. For example, in some intermittent production processes, equipment may not operate at full capacity continuously, resulting in a lower standard total utilization factor (SGF); while in continuous production processes, equipment utilization may be higher. The SGF reflects the simultaneous operating characteristics of multiple pieces of equipment. In practical applications, the multiple electrical devices connected to the busbar do not operate at full capacity simultaneously. The SGF reflects the proportion of equipment simultaneously engaged in load, correcting for the ideal situation of all equipment operating at full capacity simultaneously, thus more closely approximating the simultaneity of actual loads.

[0113] The standard effective number of electrical equipment units takes into account the actual number of devices involved in operation. During the process, not all installed equipment may be put into use simultaneously, or different devices may have different power contributions. The standard effective number of electrical equipment units allows for a more reasonable assessment of the overall impact of the equipment on the total installed power, making the calculation results closer to reality.

[0114] During project operation, instantaneous peak load situations may occur, such as the simultaneous startup of certain equipment in production. The standard historical total installed capacity ensures that the power system still has sufficient power reserves when facing peak loads, avoiding problems such as system collapse and equipment damage due to insufficient power, and ensuring the stability and continuity of power system operation.

[0115] The comprehensive correction factor determined based on the above-mentioned standard total utilization factor, effective number of standard electrical equipment, and standard historical total installed power can comprehensively reflect the situation of equipment operating at full load simultaneously, the number of equipment actually participating in operation, and the situation of instantaneous peak load. By using this comprehensive correction factor to correct the total installed power of the target process, the obtained target total installed power is more in line with the actual working conditions, thus improving the accuracy of the target total installed power.

[0116] In one alternative approach, the comprehensive correction factor for the total installed power of the target process can be calculated based on the standard total utilization factor, the effective number of standard electrical equipment, and the standard historical total installed power. Specifically, a calculation model for calculating the comprehensive correction factor for the total installed power can be pre-constructed based on historical data, including the total utilization factor, the effective number of electrical equipment, the total installed power, and the comprehensive correction factor for the total installed power. In practical applications, the standard total utilization factor, the effective number of standard electrical equipment, and the standard historical total installed power of the target process can be input into this calculation model to obtain the comprehensive correction factor for the total installed power. This method allows for the rapid acquisition of the comprehensive correction factor for the total installed power.

[0117] Alternatively, a table can be pre-established based on historical data to represent the total utilization factor, the effective number of electrical devices, the total installed capacity, and the comprehensive correction factor for the total installed capacity. In practical applications, the comprehensive correction factor for the total installed capacity can be quickly obtained by looking up the table.

[0118] Step S32: Use a comprehensive correction coefficient to correct the total installed power of the target process to obtain the target total installed power.

[0119] In one alternative approach, the target total installed power can be obtained by multiplying the comprehensive correction factor by the total installed power of the target process.

[0120] In this embodiment of the application, by calculating the comprehensive correction coefficient and using the comprehensive correction coefficient to correct the total installed power of the target process, it is possible not only to accurately reflect the actual power demand of the equipment during operation, but also to reasonably assess the overall impact of the equipment on the total installed power, making the target total installed power more consistent with the actual working conditions and more accurate.

[0121] In one feasible implementation, step S31 includes:

[0122] Step S311: Obtain the maximum coefficient associated with the standard total utilization factor and the effective number of standard electrical equipment.

[0123] The maximum load factor reflects the maximum output characteristics of the equipment load. Even if the equipment does not operate simultaneously, individual equipment may still reach its maximum load at a certain moment, such as during short-term overload or peak load. The maximum load factor is used to quantify the ratio of this maximum load to the average load. It describes the volatility and uncertainty of the load.

[0124] In one alternative approach, a relationship table can be pre-established based on the total utilization factor, the effective number of electrical devices, and the maximum coefficient. In practical applications, after determining the standard total utilization factor and the standard effective number of electrical devices, the maximum coefficient can be obtained by looking up the relationship table using these parameters.

[0125] Step S312: Calculate the comprehensive total load factor based on the maximum coefficient and the standard total utilization factor.

[0126] It is important to note that busbar calculations require considering both load simultaneity and maximum load to accurately determine the equivalent load factor that the busbar actually needs to bear. The comprehensive total load factor takes into account both load simultaneity and maximum load. In practical applications, considering only the standard total utilization factor ignores extreme cases of maximum load, leading to insufficient busbar capacity; considering only the maximum factor ignores the actual pattern of multiple devices not operating at full load simultaneously, resulting in excessively high busbar selection costs. Therefore, calculating the comprehensive total load factor by comprehensively considering both the maximum factor and the standard total utilization factor is to simultaneously account for the impact of load discrepancies and the occurrence of maximum load, obtaining a comprehensive load factor that better reflects the actual operating scenario, providing an accurate load basis for subsequent steps such as busbar selection.

[0127] In one alternative approach, the overall total load factor can be obtained by multiplying the maximum factor and the standard total utilization factor.

[0128] Step S313: Calculate the installation deviation correction coefficient based on the standard historical total installed power, standard total utilization factor, target process total installed power, and comprehensive total load factor.

[0129] Step S314: The overall total load factor is corrected using the installed capacity deviation correction factor to obtain the overall correction factor.

[0130] The purpose of calculating the installed capacity deviation correction coefficient is to address the load characteristic mismatch problem caused by changes in installed capacity, ensuring that load calculations are adapted to the new installed capacity scale and providing accurate load basis for bus selection. When the total installed power of the target process in a new project changes, the comprehensive total load factor will change synchronously. If the target total installed power of the target process is predicted directly based on the comprehensive total load factor determined by historical projects, it will lead to a deviation between the estimated total installed power and the target total installed power of the target process, resulting in underestimation or overestimation of the load. Therefore, this embodiment does not use the comprehensive total load factor determined by historical projects to predict the target total installed power of the target process. Instead, a calibration step is introduced to calculate the installed capacity deviation correction coefficient based on the standard historical total installed power, standard total utilization factor, total installed power of the target process, and comprehensive total load factor. The installed capacity deviation correction coefficient is then used to correct the comprehensive total load factor to obtain the comprehensive correction coefficient; finally, the total installed power of the target process is corrected based on the comprehensive correction coefficient to obtain the target total installed power.

[0131] In this embodiment, an installation deviation correction factor Kj is introduced for correction. The installation deviation correction factor Kj can be obtained by the following formula:

[0132] (1)

[0133] Among them, in the above formula (1) This represents the total installed power of the target process, which is the sum of the rated power of all electrical equipment required for the target process. This represents the standard historical total installed capacity, which is the sum of the rated power of all electrical equipment in the historical projects. Indicates the standard total utilization factor. This represents the overall total load factor. This represents the installation deviation correction factor.

[0134] Therefore, the comprehensive correction factor for the total installed power of the target process can be obtained by the following formula:

[0135] Kj1 = k1 * Kj. (2)

[0136] Where Kj1 is the comprehensive correction coefficient.

[0137] In this embodiment, a calibration step is introduced. Based on the standard historical total installed power, standard total utilization factor, target process total installed power, and comprehensive total load factor, an installation deviation correction factor is calculated. This installation deviation correction factor is then used to correct the comprehensive total load factor, resulting in a comprehensive correction factor, thus improving the accuracy of the comprehensive correction factor.

[0138] In one feasible implementation, step S40 includes steps S41 to S42:

[0139] Step S41: Calculate the bus current required for the target process based on the target total installed power;

[0140] In one alternative approach, the target total installed power can be input into a preset calculation model, and the bus current required for the target process can be output.

[0141] For example, assuming the bus current required for the target process is represented by I1, it can be obtained through formula (3):

[0142] (3)

[0143] in, The calculation result is the target total installed power. This represents the total installed power of the target process. Voltage U and power factor are also considered. The voltage U is a constant, and the power factor can be 390V. The value can be 0.93. The input to the preset calculation model can be the target total installed power, and the output can be the bus current of the target process. The median value. Output can be selected or not as needed. It should be noted that the preset calculation model of the above formula (3) is for three-phase electrical equipment. For single-phase electrical equipment, the above preset calculation model can be simply transformed to obtain the preset calculation model for single-phase electrical equipment.

[0144] Step S42: Determine the bus parameters that are compatible with the target process based on the bus current.

[0145] In one alternative approach, to avoid overload risks due to under-selection and to avoid investment waste and operational losses due to over-selection, the most suitable bus capacity is typically chosen between 65% and 85% of the load rate. Load rate = bus current / bus capacity, therefore bus capacity = bus current / load rate (65%~85%). For example, if the calculated bus current is 1850A, then the bus capacity is taken from 2176A to 2846A.

[0146] In another alternative approach, a table relating bus current and bus parameters is pre-set. By consulting the table relating bus current and bus parameters, the bus parameters that are compatible with the target process can be determined based on the bus current of the target process. This simplifies the calculation process and improves processing efficiency.

[0147] Assuming the bus parameters are bus capacity, the relationship between the preset bus current and the preset bus capacity is shown in Table 1 below:

[0148] Table 1

[0149]

[0150] Referring to Table 1, if the calculated bus current is 1000A (unit: amperes, for example), in order to ensure that the bus can safely carry 1000A of current, the bus capacity corresponding to 1114A in the table can be selected as the bus parameter, in which case only one bus is needed; or, multiple bus capacities corresponding to 870A in the table can be selected as the bus parameter to ensure that the final bus can carry 1000A of current. The specific bus capacity and number of bus can be set according to the actual test results or empirical values, and are not limited in this application.

[0151] Taking the target processes as mixing, cold pressing, die cutting, assembly, and baking as an example, Table 2 shows the selection and configuration table for the number of busbars:

[0152] Table 2

[0153]

[0154] It is worth noting that the table above is only an example; in practical applications, the data in the table can be designed according to needs.

[0155] In this embodiment, the bus current required for the target process is calculated by correcting the target total installed power, and then the bus parameters suitable for the target process are determined based on the bus current, thereby improving the accuracy of bus selection.

[0156] The method for determining busbar parameters of this application will be described in its entirety below with reference to the above embodiments.

[0157] (1) Obtain the operating parameters of historical projects. The operating parameters of historical projects include the historical total utilization factor, the effective number of historical electrical equipment, and the historical total installed capacity.

[0158] (2) Calculate the operating parameters of the target process based on the obtained historical project operating parameters, including the standard total utilization factor, the effective number of standard electrical equipment, and the standard historical total installed power. The specific calculation method is as follows:

[0159] The calculation method for the standard total utilization factor is as follows: Based on the dispersion and central tendency of multiple historical total utilization factors, a first normal distribution model is constructed; from the first normal distribution model, the target historical total utilization factor corresponding to the cumulative probability is obtained; the target historical total utilization factor is used as the standard total utilization factor of the target process.

[0160] The calculation method for the effective number of standard electrical equipment is as follows: Based on the dispersion and central tendency of the effective number of multiple historical electrical equipment, a second normal distribution model is constructed; from the second normal distribution model, the target historical effective number of electrical equipment corresponding to the set cumulative probability is obtained.

[0161] The calculation method for the standard historical total installed capacity is as follows: the effective number of target historical electrical equipment is used as the standard effective number of electrical equipment in the target process.

[0162] (3) The maximum coefficient is obtained by looking up the standard total utilization factor and the effective number of standard electrical equipment in the table.

[0163] (4) The comprehensive total load factor is obtained by multiplying the maximum coefficient and the standard total utilization factor.

[0164] (5) Calculate the installation deviation correction coefficient based on the standard historical total installed power, standard total utilization factor, target process total installed power and comprehensive total load factor. The specific calculation formula is the above formula (1).

[0165] (6) The overall total load factor is corrected by the installed capacity deviation correction factor to obtain the overall correction factor. The specific calculation formula is the above formula (2).

[0166] (7) The total installed power of the target process is corrected by a comprehensive correction factor to obtain the target total installed power.

[0167] (8) Calculate the bus current required for the target process based on the target total installed capacity. The specific calculation formula is formula (3) above.

[0168] (9) Determine the bus parameters that are compatible with the target process based on the bus current.

[0169] The aforementioned historical project operating parameters, including historical total utilization factor, historical effective number of electrical equipment, and historical total installed capacity, as well as the total installed capacity of the target process, can be used as inputs to the preset calculation model. Bus current and bus parameters can be used as outputs of the preset calculation model. Other parameters, including maximum coefficient, comprehensive total load factor, installed capacity deviation correction factor, and target total installed capacity, can be output or not, depending on the actual situation. In practical applications, corresponding web pages or applications can be developed to output relevant parameters and calculate and output the corresponding calculation results through the underlying preset calculation model, thereby improving the efficiency of determining bus parameters for processes such as mixing, cold pressing, die-cutting, assembly, and baking.

[0170] This application also provides a busbar parameter determination device, please refer to... Figure 6 The busbar parameter determination device includes:

[0171] The acquisition module 10 is used to acquire the operating condition parameters of historical projects corresponding to the equipment type of the electrical equipment required in the target process.

[0172] The processing module 20 is used to estimate the operating parameters of the target process based on the operating parameters of historical projects; correct the total installed power of the target process based on the operating parameters of the target process to obtain the target total installed power; and determine the bus parameters that are compatible with the target process based on the target total installed power.

[0173] In one embodiment, when there are multiple historical projects, there are multiple operating parameters for the historical projects; the processing module 20 is further configured to: determine the dispersion and central tendency of the operating parameters of the multiple historical projects; and obtain the operating parameters of the target process from the operating parameters of the multiple historical projects based on the dispersion and central tendency of the operating parameters of the multiple historical projects.

[0174] In one embodiment, the operating parameters of the historical project include the historical total utilization coefficient, and the operating parameters of the target process include the standard total utilization coefficient; the processing module 20 is further configured to: construct a first normal distribution model based on the dispersion and central tendency of the multiple historical total utilization coefficients; obtain the target historical total utilization coefficient corresponding to the cumulative probability set by the first normal distribution model; and use the target historical total utilization coefficient as the standard total utilization coefficient of the target process.

[0175] In one embodiment, the operating condition parameters of the historical project include the effective number of historical electrical equipment units, and the operating condition parameters of the target process include the effective number of standard electrical equipment units. The processing module 20 is further configured to: construct a second normal distribution model based on the dispersion and central tendency of multiple effective numbers of historical electrical equipment units; obtain the target effective number of historical electrical equipment units corresponding to the cumulative probability set in the second normal distribution model; and use the target effective number of historical electrical equipment units as the effective number of standard electrical equipment units for the target process.

[0176] In one embodiment, the operating parameters of historical projects include historical total installed power; the processing module 20 is further configured to: select the largest historical total installed power from the historical total installed power of multiple historical projects as the standard historical total installed power.

[0177] In one embodiment, the processing module 20 is further configured to: calculate a comprehensive correction coefficient for the total installed power of the target process based on the operating parameters of the target process, wherein the operating parameters of the target process include the standard total utilization coefficient, the effective number of standard electrical equipment and the standard historical total installed power; and correct the total installed power of the target process using the comprehensive correction coefficient to obtain the target total installed power.

[0178] In one embodiment, the processing module 20 is further configured to: obtain the maximum coefficient associated with the standard total utilization factor and the effective number of standard electrical equipment; calculate the comprehensive total load factor based on the maximum coefficient and the standard total utilization factor; calculate the installation deviation correction factor based on the standard historical total installed power, the standard total utilization factor, the total installed power of the target process and the comprehensive total load factor; and correct the comprehensive total load factor using the installation deviation correction factor to obtain the comprehensive correction factor.

[0179] In one embodiment, the processing module 20 is further configured to: calculate the bus current required for the target process based on the target total installed power; and determine the bus parameters adapted to the target process based on the bus current.

[0180] In one embodiment, the processing module 20 is further configured to: determine the bus parameters that are compatible with the target process based on the relationship table between the bus current, the preset bus current and the preset bus parameters.

[0181] The beneficial effects of the bus parameter determination device provided in this application are the same as those of the bus parameter determination method provided in the above embodiments, and other technical features in the bus parameter determination device are the same as those disclosed in the above embodiments, and will not be repeated here.

[0182] This application provides a bus parameter determination device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the bus parameter determination method in any of the above embodiments.

[0183] The following is for reference. Figure 7 The diagram illustrates a structural schematic suitable for implementing the bus parameter determination device in the embodiments of this application. The bus parameter determination device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, personal digital assistants (PDAs), tablet computers (PADs), portable media players (PMPs), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 7 The bus parameter determination device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0184] like Figure 7As shown, the bus parameter determination device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 1002 or a program loaded from storage device 1003 into random access memory (RAM) 1004. The random access memory 1004 also stores various programs and data required for the operation of the bus parameter determination device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the bus parameter determination device to communicate wirelessly or wiredly with other devices to exchange data. Although a bus parameter determination device with various systems is shown in the figure, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0185] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0186] The beneficial effects of the bus parameter determination device provided in this application are the same as those of the bus parameter determination method provided in the above embodiments, and other technical features of the bus parameter determination device are the same as those disclosed in the method of the previous embodiment, which will not be repeated here.

[0187] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0188] The above are merely specific embodiments 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.

[0189] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the bus parameter determination method in the above embodiments.

[0190] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory (EPROM), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0191] The aforementioned computer-readable storage medium may be included in the bus parameter determination device; or it may exist independently and not assembled into the bus parameter determination device.

[0192] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the bus parameter determination device, cause the bus parameter determination device to implement the bus parameter determination method of any of the above embodiments.

[0193] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0194] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0195] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0196] The beneficial effects of the computer-readable storage medium provided in this application are the same as those of the bus parameter determination method provided in the above embodiments, and will not be repeated here.

[0197] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the bus parameter determination method described above.

[0198] The beneficial effects of the computer program product provided in this application are the same as those of the bus parameter determination method provided in the above embodiments, and will not be repeated here.

[0199] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for determining busbar parameters, characterized in that, The method for determining the busbar parameters includes: Based on the equipment type of the electrical equipment required in the target process, obtain the operating condition parameters of the historical projects corresponding to the equipment type; Based on the operating parameters of the historical projects, the operating parameters of the target process are estimated. Based on the operating parameters of the target process, a comprehensive correction coefficient for the total installed power of the target process is calculated, wherein the operating parameters of the target process include the standard total utilization factor, the effective number of standard electrical equipment, and the standard historical total installed power. The total installed power of the target process is corrected using the comprehensive correction coefficient to obtain the target total installed power; Based on the target total installed capacity, determine the bus parameters that are compatible with the target process.

2. The method for determining busbar parameters as described in claim 1, characterized in that, When there are multiple historical projects, there are multiple operating condition parameters for each historical project; estimating the operating condition parameters of the target process based on the operating condition parameters of the historical projects includes: Determine the dispersion and central tendency of the operating parameters of multiple historical projects; Based on the dispersion and central tendency of the operating parameters of multiple historical projects, the operating parameters of the target process are obtained from the operating parameters of multiple historical projects.

3. The method for determining busbar parameters as described in claim 2, characterized in that, The operating parameters of the historical projects include the historical total utilization coefficient, and the operating parameters of the target process include the standard total utilization coefficient; obtaining the operating parameters of the target process from the operating parameters of the multiple historical projects based on the dispersion and central tendency of the operating parameters of the multiple historical projects includes: Based on the dispersion and central tendency of the various historical total utilization coefficients, a first normal distribution model is constructed; From the first normal distribution model, obtain the cumulative probability as the target historical total utilization coefficient corresponding to the set cumulative probability; The target historical total utilization factor is used as the standard total utilization factor of the target process.

4. The method for determining busbar parameters as described in claim 2, characterized in that, The operating condition parameters of the historical projects include the effective number of historical electrical equipment units, and the operating condition parameters of the target process include the effective number of standard electrical equipment units; obtaining the operating condition parameters of the target process from the operating condition parameters of the multiple historical projects based on the dispersion and central tendency of the operating condition parameters of the multiple historical projects includes: Based on the dispersion and central tendency of the effective number of multiple historical electrical devices, a second normal distribution model is constructed. From the second normal distribution model, obtain the cumulative probability as the target historical effective number of electrical devices corresponding to the set cumulative probability; The effective number of the target historical electrical equipment is used as the standard effective number of electrical equipment in the target process.

5. The method for determining busbar parameters as described in claim 1, characterized in that, The operating parameters of the historical projects include the historical total installed capacity, and the operating parameters of the target process include the standard historical total installed capacity; estimating the operating parameters of the target process based on the operating parameters of the historical projects includes: The highest historical total installed capacity is selected from the historical total installed capacity of multiple historical projects as the standard historical total installed capacity.

6. The method for determining busbar parameters as described in claim 1, characterized in that, The comprehensive correction factor for calculating the total installed power of the target process based on the operating parameters of the target process includes: Obtain the maximum coefficient associated with the total standard utilization factor and the effective number of standard electrical devices; Calculate the overall total load factor based on the maximum coefficient and the standard total utilization factor; Calculate the installation deviation correction coefficient based on the standard historical total installed power, the standard total utilization factor, the target process's total installed power, and the comprehensive total load factor; The overall total load factor is corrected using the installed capacity deviation correction factor to obtain the overall correction factor.

7. The method for determining busbar parameters as described in claim 1, characterized in that, The determination of bus parameters adapted to the target process based on the target total installed capacity includes: Based on the target total installed capacity, calculate the bus current required for the target process; Based on the bus current, determine the bus parameters that are compatible with the target process.

8. The method for determining bus parameters as described in claim 7, characterized in that, The step of determining the bus parameters adapted to the target process based on the bus current includes: Based on the relationship table between the bus current, the preset bus current and the preset bus parameters, determine the bus parameters that are compatible with the target process.

9. A busbar parameter determination device, characterized in that, The busbar parameter determination device includes: The acquisition module is used to acquire the operating condition parameters of historical projects corresponding to the equipment type of the electrical equipment required in the target process. The processing module is used to estimate the operating parameters of the target process based on the operating parameters of the historical projects; calculate a comprehensive correction coefficient for the total installed power of the target process based on the operating parameters of the target process, wherein the operating parameters of the target process include the standard total utilization factor, the effective number of standard electrical equipment, and the standard historical total installed power; correct the total installed power of the target process using the comprehensive correction coefficient to obtain the target total installed power; and determine the bus parameters adapted to the target process based on the target total installed power.

10. A busbar parameter determination device, characterized in that, The bus parameter determination device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the bus parameter determination method as described in any one of claims 1 to 8.

11. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the bus parameter determination method as described in any one of claims 1 to 8.

12. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the bus parameter determination method as described in any one of claims 1 to 8.

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