Energy consumption determination method, electronic equipment and storage medium

Abstract

The invention discloses an energy consumption determination method, electronic equipment and a storage medium. The method comprises the following steps: acquiring energy consumption data and an energy type of energy; performing quality detection on the energy consumption data to obtain a detection result, the detection result being used for representing whether the energy consumption data meets a preset quality standard; based on the detection result and the energy type, determining a target bidding coefficient of the energy, the target bidding coefficient being used for representing a conversion factor for converting the energy into a standard coal equivalent; and converting the energy consumption data based on the target bidding coefficient to obtain the energy consumption of the energy, the energy consumption being used for representing the value of the energy under the standard coal equivalent. According to the invention, the technical problem of low calculation accuracy of energy consumption in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of energy, and in particular to a method for determining energy consumption, an electronic device and a storage medium. Background Art

[0002] The energy management system is a key platform for chemical companies to conduct energy management. It integrates energy consumption information and supports multiple functions such as energy planning, monitoring, statistical analysis, and assessment to achieve closed-loop management of energy use.

[0003] However, the energy consumption parameters in the energy consumption statistics method in the related technology cannot reflect the energy quality information in real time, and some indicator data need to be manually corrected. At the same time, the energy statistics between the devices lack effective correlation calculations and fail to fully consider the internal connections of energy consumption, resulting in the lack of accuracy of energy consumption data and deviations in calculation results, which in turn leads to low accuracy in energy consumption calculation in the related technology.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method for determining energy consumption, an electronic device and a storage medium, so as to at least solve the technical problem of low accuracy in calculating energy consumption in the related art.

[0006] According to one aspect of an embodiment of the present invention, there is provided a method for determining energy consumption, comprising: obtaining energy consumption data and energy type of energy; performing quality detection on the energy consumption data to obtain detection results, wherein the detection results are used to indicate whether the energy consumption data meets preset quality standards; determining a target discount coefficient of the energy based on the detection results and the energy type, wherein the target discount coefficient is used to indicate a conversion factor for converting the energy into standard coal equivalent; converting the energy consumption data based on the target discount coefficient to obtain energy consumption of the energy, wherein the energy consumption is used to indicate the value of the energy in standard coal equivalent.

[0007] Furthermore, a target discount coefficient for energy is determined based on the detection results and energy types, including: in response to the detection result that the energy consumption data meets the preset quality standard, retrieving the energy discount coefficient calculation model based on the energy type, inputting the energy consumption data into the discount coefficient calculation model, and obtaining the target discount coefficient; in response to the detection result that the energy consumption data does not meet the preset quality standard, retrieving the preset discount coefficient for energy based on the energy type, and determining the preset discount coefficient as the target discount coefficient.

[0008] Furthermore, after the energy consumption data is input into the discount coefficient calculation model and the target discount coefficient is obtained, the method also includes: retrieving the preset discount coefficient of the energy from the database based on the energy type; updating the preset discount coefficient based on the target discount coefficient to obtain an updated preset discount coefficient; and storing the updated preset discount coefficient in the database.

[0009] Further, the preset quality standards include at least one of the following: integrity quality standard, timeliness quality standard, effectiveness quality standard, and quality inspection of energy consumption data is performed to obtain inspection results, including: performing integrity inspection on energy consumption data to obtain integrity inspection results, wherein the integrity inspection results are used to indicate whether the energy consumption data meets the integrity quality standard; performing timeliness inspection on energy consumption data to obtain timeliness inspection results, wherein the timeliness inspection results are used to indicate whether the energy consumption data meets the timeliness quality standard; performing effectiveness inspection on energy consumption data to obtain effectiveness inspection results, wherein the effectiveness inspection results are used to indicate whether the energy consumption data meets the effectiveness quality standard; determining the inspection results based on any one or more of the integrity inspection results, timeliness inspection results, and effectiveness inspection results.

[0010] Furthermore, an integrity check is performed on the energy consumption data to obtain an integrity check result, including: obtaining at least one quality indicator of the energy; in response to the energy consumption data being data corresponding to at least one quality indicator, determining that the integrity check result is that the energy consumption data meets the integrity quality standard; in response to the energy consumption data not being data corresponding to at least one quality indicator, determining that the integrity check result is that the energy consumption data does not meet the integrity quality standard.

[0011] Furthermore, a timeliness check is performed on the energy consumption data to obtain a timeliness check result, including: obtaining a receiving time point of the energy consumption data; in response to the receiving time point being within a preset time interval, determining that the timeliness check result is that the energy consumption data meets the timeliness quality standard; in response to the receiving time point not being within the preset time interval, determining that the timeliness check result is that the energy consumption data does not meet the timeliness quality standard.

[0012] Furthermore, the energy consumption data is tested for validity to obtain a validity test result, including: obtaining a preset data interval of energy; in response to the energy consumption data being in the preset data interval, determining that the validity test result is that the energy consumption data meets the validity quality standard; in response to the energy consumption data not being in the preset data interval, determining that the validity test result is that the energy consumption data does not meet the validity quality standard.

[0013] According to another aspect of an embodiment of the present invention, there is also provided an energy consumption determination device, comprising: an acquisition module, used to acquire energy consumption data and energy type of energy; a detection module, used to perform quality detection on the energy consumption data to obtain a detection result, wherein the detection result is used to indicate whether the energy consumption data meets a preset quality standard; a determination module, used to determine a target discount coefficient of the energy based on the detection result and the energy type, wherein the target discount coefficient is used to indicate a conversion factor for converting the energy into standard coal equivalent; a conversion module, used to convert the energy consumption data based on the target discount coefficient to obtain the energy consumption of the energy, wherein the energy consumption is used to indicate the value of the energy in standard coal equivalent.

[0014] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0015] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0017] In an embodiment of the present invention, the energy consumption data and energy type of the energy are first obtained, and then the energy consumption data is quality tested to obtain the test results. Then, the target discount coefficient is determined based on the test results and the energy type. Finally, the energy consumption data is converted based on the target discount coefficient to obtain the energy consumption of the energy. It is easy to notice that the present application starts from the two perspectives of energy consumption data and energy type, and obtains energy consumption data that meets the preset quality standards by performing quality tests on the acquired energy consumption data. At the same time, the target discount coefficients corresponding to different types of energy are determined. Finally, the energy consumption is accurately calculated based on the energy consumption data that meets the quality standards and the target discount coefficients corresponding to the energy consumption data, thereby achieving the technical effect of improving the timeliness and accuracy of the energy consumption calculation, and further solving the technical problem of low accuracy in energy consumption calculation in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a flow chart of a method for determining energy consumption according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of a device for determining energy consumption according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an embodiment of the present invention, an embodiment of a method for determining energy consumption is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] Figure 1 is a flow chart of a method for determining energy consumption according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0025] Step S102, obtaining energy consumption data and energy type of energy;

[0026] The above energy consumption data may refer to the amount of various energy consumed by the production system, auxiliary production system and ancillary production system during operation within a specific time period. The energy consumption data may be used to monitor energy usage and serve as the basis for the next step of energy statistics, analysis and management.

[0027] The above-mentioned energy types may refer to energy that can be divided into multiple types according to its source and nature. The energy types may include but are not limited to primary energy such as raw coal, oil, natural gas, etc., secondary energy such as electricity, heat, petroleum products, coke, coal gas, etc., and energy-consuming working fluids such as water, oxygen, nitrogen, compressed air, desalted water, etc. The above-mentioned energy classification methods and energy types are only examples. The specific energy type needs to be determined according to the consumption method, actual demand and energy nature, and is not limited here. The purpose of obtaining the energy type may include but is not limited to calculating the comprehensive energy consumption of different energy types, evaluating the effectiveness of energy-saving and emission reduction measures, etc.

[0028] The above-mentioned acquisition methods may include but are not limited to the following methods:

[0029] The first method is real-time collection, which uses smart meters and sensors installed on energy pipelines and equipment to collect energy consumption data in real time and transmit it to the energy management system.

[0030] The second method is historical data reference, which obtains energy consumption data through historical energy consumption data stored in the system.

[0031] The third method is data interface integration, which automatically pulls the required energy consumption data and energy type information through data interface integration with the company's production management system, quality management system, etc.

[0032] The above energy consumption data and energy type acquisition methods are only examples. The specific acquisition method needs to be determined according to actual needs and is not limited here.

[0033] In an optional embodiment, by installing smart meters and sensors on energy pipelines and equipment, energy consumption data and energy types can be collected and acquired in real time. The energy consumption data can be matched with the energy type, so that the consumption of various types of energy can be intuitively seen, and then the comprehensive energy consumption of different energy types can be calculated, and the effectiveness of energy-saving and emission reduction measures can be evaluated, providing strong data support for subsequent energy management decisions.

[0034] Step S104, performing quality inspection on the energy consumption data to obtain inspection results, wherein the inspection results are used to indicate whether the energy consumption data meets a preset quality standard.

[0035] The above-mentioned test results may refer to the output of the energy consumption data quality test process, which is used to indicate whether the data meets the preset quality standards. The types of test results may include but are not limited to integrity test results, timeliness test results, effectiveness test results, etc. The specific test result type needs to be determined according to the quality test type, which is not limited here. The role of the test results may include but is not limited to confirming the reliability of data, anomaly detection, decision support, etc.

[0036] The above-mentioned quality inspection may refer to the process of checking energy consumption data to verify whether it meets the preset quality standards. The types of quality inspection may include but are not limited to integrity inspection, timeliness inspection, and effectiveness inspection. The specific type of quality inspection needs to be determined based on the purpose of the inspection and the type of data. No limitation is made here. The role of quality inspection may include but is not limited to error identification and correction, improving decision-making quality, etc.

[0037] The above-mentioned preset quality standards may refer to a series of rules and thresholds used to evaluate the quality of energy consumption data during the quality inspection process. The types of preset quality standards may include but are not limited to preset data intervals, preset time intervals, etc. The specific preset quality standards may be determined based on industry specifications, regulatory requirements, corporate policies, and specific application scenarios of the data. No limitation is made here. The role of preset quality standards may include but is not limited to providing evaluation benchmarks, ensuring data compliance, and optimizing data processing.

[0038] In an optional embodiment, performing quality inspection on energy consumption data and obtaining inspection results is a key step in ensuring the effectiveness of a data-driven energy management system, wherein the inspection results directly reflect whether the energy consumption data meets preset quality standards, thereby completing the screening of energy consumption data and avoiding the negative impact of low-quality data on energy consumption analysis and management decisions. This not only reduces the statistical workload of energy management personnel, but also greatly improves the accuracy and real-time nature of energy consumption statistical data.

[0039] Step S106, determining a target conversion coefficient of energy based on the detection result and the energy type, wherein the target conversion coefficient is used to represent a conversion factor for converting energy into standard coal equivalent.

[0040] The above-mentioned target discount coefficient may refer to a parameter used for energy statistics and energy consumption calculation. The types of target discount coefficients may include but are not limited to measured discount coefficients, dynamically adjusted discount coefficients, etc. The specific discount coefficients shall be determined based on the energy type and test results, and are not limited here. The target discount coefficients may be used to enable different types of energy consumption to be compared and summarized according to a unified unit of measurement, namely standard coal equivalent, to facilitate the overall assessment and management of energy consumption by enterprises.

[0041] The above-mentioned standard coal equivalent may refer to an energy measurement unit commonly used in energy efficiency analysis and energy statistics. The standard coal equivalent may be used to unify the standards of all energy consumption, facilitating comparison and aggregation of different energy consumption.

[0042] In an optional embodiment, the target discount coefficient of energy is determined by the test results and energy type. Based on the target discount coefficient specific to the energy type, the enterprise can obtain a more realistic energy consumption, thereby accurately evaluating the efficiency of energy use and formulating effective energy conservation and emission reduction measures. In addition, the use of standard coal equivalent as a unified unit of measurement for energy consumption simplifies the complexity of energy consumption statistics and analysis, facilitates cross-departmental and cross-energy type energy consumption comparisons, and supports enterprises in making more comprehensive and sophisticated energy management decisions.

[0043] Step S108, converting the energy consumption data based on the target conversion coefficient to obtain the energy consumption, wherein the energy consumption is used to represent the value of the energy in terms of standard coal equivalent.

[0044] In an optional embodiment, converting energy consumption data by using the target conversion coefficient is a key step to achieve energy consumption standardization and improve energy management efficiency. This process converts the consumption of various energy sources into values ​​in standard coal equivalent, i.e., energy consumption, which not only achieves the comparability of consumption between different energy types, but also facilitates enterprises to conduct comprehensive and unified analysis and evaluation of the overall energy consumption.

[0045] In an embodiment of the present invention, the energy consumption data and energy type of the energy are first obtained, and then the energy consumption data is quality tested to obtain the test results. Then, the target discount coefficient is determined based on the test results and the energy type. Finally, the energy consumption data is converted based on the target discount coefficient to obtain the energy consumption of the energy. It is easy to notice that the present application starts from the two perspectives of energy consumption data and energy type, and obtains energy consumption data that meets the preset quality standards by performing quality tests on the acquired energy consumption data. At the same time, the target discount coefficients corresponding to different types of energy are determined. Finally, the energy consumption is accurately calculated based on the energy consumption data that meets the quality standards and the target discount coefficients corresponding to the energy consumption data, thereby achieving the technical effect of improving the timeliness and accuracy of the energy consumption calculation, and further solving the technical problem of low accuracy in energy consumption calculation in related technologies.

[0046] In an optional embodiment, the comprehensive energy consumption of indirect coal liquefaction is equal to the various energy input in the production process minus the various energy output, and the calculation formula is as follows:

[0047]

[0048] Where, E represents the comprehensive energy consumption of coal indirect liquefaction, K i It represents the target discount coefficient of the input i-th energy and energy-consuming medium, E i represents the physical quantity of the i-th non-raw material energy and energy-consuming fluid input in the production process, n represents the number of non-raw material energy and energy-consuming fluid types input, K j The standard coal coefficient of the j-th energy output, E j It represents the physical quantity of the jth type of energy generated by non-raw material energy output in the production process, m represents the number of energy types generated by non-raw material energy output, Q represents the total amount of standard coal equivalent of the actual recovered heat generated by non-raw material energy and output to the outside of the system, and ∑ represents the summation operation.

[0049] The calculation formula for the comprehensive energy consumption per unit product of indirect coal liquefaction is as follows:

[0050]

[0051] In the formula, e represents the comprehensive energy consumption per unit product of indirect coal liquefaction to produce oil, E represents the comprehensive energy consumption of indirect coal liquefaction to produce oil, M represents the output of indirect coal liquefaction to produce oil during the reporting period, namely diesel, naphtha, liquefied petroleum gas, synthetic wax, heavy wax and other oil products, excluding by-products such as mixed alcohols, 1000 is a constant, and the specific size can be determined according to the size and unit of energy consumption, and is not limited here.

[0052] Optionally, a target discount coefficient for energy is determined based on the test results and the energy type, including: in response to the test result that the energy consumption data meets a preset quality standard, retrieving a discount coefficient calculation model for the energy based on the energy type, inputting the energy consumption data into the discount coefficient calculation model, and obtaining the target discount coefficient; in response to the test result that the energy consumption data does not meet the preset quality standard, retrieving the preset discount coefficient for the energy based on the energy type, and determining the preset discount coefficient as the target discount coefficient.

[0053] The above-mentioned standard conversion coefficient calculation model may refer to a mathematical model that can automatically convert energy into a specific conversion factor of standard coal equivalent. The function of the standard conversion coefficient calculation model may include but is not limited to dynamically adjusting the standard conversion coefficient according to the real-time changes in energy quality to ensure that the calculation results reflect the actual energy consumption.

[0054] The above-mentioned preset discount coefficient may refer to an energy conversion factor set based on industry standards or experience values. The types of preset discount coefficients may include but are not limited to industry averages, corporate historical values, national or regional standard values, etc. The specific preset discount coefficient needs to be determined based on the energy type and application scenario, and is not limited here. The role of the preset discount coefficient may include but is not limited to ensuring that the calculation of energy consumption can still be carried out when the data quality is unreliable.

[0055] In an optional embodiment, a target discount coefficient is determined based on whether the energy consumption data meets the preset quality standard. When the test result is that the energy consumption data meets the preset quality standard, the energy consumption data is processed through a discount coefficient calculation model to obtain the target discount coefficient. When the test result is that the energy consumption data does not meet the preset quality standard, the preset discount coefficient is determined as the target discount coefficient. In the above process, the discount coefficient calculation model ensures that when the data quality meets the standard, accurate energy consumption calculation can be performed based on the actual energy quality, and the preset discount coefficient serves as a backup mechanism for data quality control to maintain the normal statistical work when the data is unqualified or abnormal. The two work together to ensure the accuracy and continuity of energy consumption calculation, and provide strong support for the enterprise's energy management and energy conservation and emission reduction.

[0056] Optionally, after inputting the energy consumption data into the discount coefficient calculation model and obtaining the target discount coefficient, the method also includes: retrieving the preset discount coefficient of the energy from the database based on the energy type; updating the preset discount coefficient based on the target discount coefficient to obtain an updated preset discount coefficient; and storing the updated preset discount coefficient in the database.

[0057] The above-mentioned database may refer to a key infrastructure used to store energy consumption data, preset discount coefficients, energy type information and other related data. The functions of the database may include but are not limited to data storage and management, data retrieval and access, data update and maintenance, and data unification and sharing.

[0058] In an optional embodiment, after the system calculates a new target discount coefficient based on the real-time detection results, it will automatically retrieve the corresponding preset discount coefficient from the database based on the energy type, and then use the target discount coefficient to intelligently update the preset discount coefficient to ensure that the preset discount coefficient is synchronized with the actual energy quality and reflects the true situation of energy consumption. The above dynamic update method of discount coefficient based on real-time data drive ensures that the discount coefficient in the database is always kept up to date, while improving the intelligence level and efficiency of energy management of chemical enterprises.

[0059] Optionally, the preset quality standards include at least one of the following: an integrity quality standard, a timeliness quality standard, and an effectiveness quality standard, and the energy consumption data is quality checked to obtain a test result, including: performing an integrity test on the energy consumption data to obtain an integrity test result, wherein the integrity test result is used to indicate whether the energy consumption data meets the integrity quality standard; performing a timeliness test on the energy consumption data to obtain a timeliness test result, wherein the timeliness test result is used to indicate whether the energy consumption data meets the timeliness quality standard; performing a effectiveness test on the energy consumption data to obtain a effectiveness test result, wherein the effectiveness test result is used to indicate whether the energy consumption data meets the effectiveness quality standard; and determining the test result based on any one or more of the integrity test result, the timeliness test result, and the effectiveness test result.

[0060] The above-mentioned integrity quality standards may refer to standards for measuring whether energy consumption data is complete. The integrity quality standards may include but are not limited to whether the data records are comprehensive, whether there are missing or omitted data points, etc. The specific integrity quality standards need to be determined based on the nature of the energy consumption data and are not limited here. The role of the integrity quality standards may include but is not limited to ensuring that all relevant energy consumption data are accurately recorded without any omissions, ensuring the integrity of the energy consumption data, etc.

[0061] The above-mentioned timeliness quality standards may refer to standards that ensure that the acquisition, processing and analysis of energy consumption data should be completed within an acceptable time frame. The types of timeliness quality standards may include but are not limited to data update frequency, data collection time interval, etc. The specific timeliness quality standards may be determined based on the specific timeliness nature of the data, and are not limited here. The role of timeliness quality standards may include but is not limited to ensuring the real-time nature of the data, enabling enterprises to respond immediately to changes in energy consumption and adjust energy use strategies and production plans in a timely manner.

[0062] The above-mentioned validity quality standards may refer to standards for ensuring the correctness and applicability of energy consumption data. The types of validity quality standards may include but are not limited to data format standards, data range standards, etc. The role of validity quality standards may include but are not limited to ensuring the accuracy and applicability of data, avoiding erroneous decisions due to erroneous data, etc.

[0063] The above-mentioned integrity test may refer to the process of verifying whether the energy consumption data meets the integrity quality standard. The integrity test may be used to discover and repair breakpoints or omissions in the data collection process, and avoid energy consumption calculation deviations caused by incomplete data.

[0064] The above-mentioned timeliness detection may refer to the process of evaluating whether energy consumption data is collected and processed within a specified time frame. Timeliness detection may be used to ensure the timely availability of data and avoid affecting the real-time monitoring and management of energy consumption due to data delays.

[0065] The above-mentioned validity detection can refer to the process of checking whether the energy consumption data conforms to a specific range and format, and whether the data logic is consistent. The validity detection can be used to ensure the reliability and accuracy of the data, avoid statistical errors and decision-making errors, etc.

[0066] In an optional embodiment, by setting integrity quality standards, timeliness quality standards and effectiveness quality standards, and implementing corresponding integrity tests, timeliness tests and effectiveness tests, the energy management system can ensure that the energy consumption data it processes meets high standards in terms of integrity, timeliness and effectiveness, thereby providing a solid data foundation for the company's energy consumption statistics, energy efficiency analysis and formulation of energy-saving and emission reduction strategies, and thus helping to improve the accuracy and efficiency of data-driven decision-making.

[0067] Optionally, an integrity check is performed on the energy consumption data to obtain an integrity check result, including: obtaining at least one quality indicator of the energy; in response to the energy consumption data being data corresponding to at least one quality indicator, determining that the integrity check result is that the energy consumption data meets the integrity quality standard; in response to the energy consumption data not being data corresponding to at least one quality indicator, determining that the integrity check result is that the energy consumption data does not meet the integrity quality standard.

[0068] The above-mentioned quality indicators may refer to a series of specific parameters or standards used to measure and evaluate the quality of energy consumption data. The types of quality indicators may include but are not limited to data coverage, data consistency indicators, data integrity indicators, etc. Specific quality indicators need to be determined based on the data type and industry standards, and are not limited here. The role of quality indicators may include but is not limited to determining whether the data is complete, data verification, and ensuring the comprehensiveness of data collection.

[0069] In an optional embodiment, by obtaining at least one quality indicator related to energy, the integrity of the data can be systematically evaluated. When the energy consumption data covers all the necessary quality indicator information, the integrity test results confirm that the data meets the integrity quality standard, ensuring the comprehensiveness and completeness of the data, and providing a solid foundation for subsequent energy statistics and management. On the contrary, if the test finds that the data is missing content related to any quality indicator, the integrity test results will indicate that the data does not meet the integrity standard, triggering a data supplement or correction mechanism to avoid statistical deviations and management decision errors caused by incomplete data.

[0070] Optionally, a timeliness check is performed on the energy consumption data to obtain a timeliness check result, including: obtaining a receiving time point of the energy consumption data; in response to the receiving time point being within a preset time interval, determining that the timeliness check result is that the energy consumption data meets a timeliness quality standard; in response to the receiving time point not being within the preset time interval, determining that the timeliness check result is that the energy consumption data does not meet a timeliness quality standard.

[0071] The above-mentioned receiving time point may refer to the specific time when the energy consumption data is received by the system. The receiving time point may be used for data timeliness evaluation, system performance monitoring, and business decision support, etc.

[0072] The above-mentioned preset time interval may refer to a time window set by the system to ensure data timeliness, that is, the time range in which data should be completed from generation to reception. The types of preset time intervals may include but are not limited to fixed time windows, dynamic time windows, and business-specific time windows. The specific preset time interval needs to be determined based on the nature of the energy consumption data and is not limited here. The role of the preset time interval may include but is not limited to serving as a data timeliness standard, coordinating business processes, etc.

[0073] In an optional embodiment, the timeliness test result is obtained by obtaining the receiving time point of the energy consumption data and judging whether the receiving time point is within the preset time interval. If the receiving time point is within the preset time interval, it indicates that the energy consumption data meets the timeliness quality standard. If the receiving time point is not within the preset time interval, it indicates that the energy consumption data does not meet the timeliness quality standard. Through the above timeliness test process, chemical companies can ensure that their energy consumption data is accurately received within the preset time interval, meeting the strict requirements of energy management on data real-time and effectiveness, thereby improving the efficiency and accuracy of data-driven decision-making.

[0074] Optionally, a validity check is performed on the energy consumption data to obtain a validity check result, including: obtaining a preset data interval of energy; in response to the energy consumption data being in the preset data interval, determining that the validity check result is that the energy consumption data meets the validity quality standard; in response to the energy consumption data not being in the preset data interval, determining that the validity check result is that the energy consumption data does not meet the validity quality standard.

[0075] The above-mentioned preset data interval may refer to a reasonable range of energy consumption data pre-set based on historical data, industry standards, equipment performance or specific business rules. The preset data interval may be composed of a maximum value and a minimum value, which is used to limit the fluctuation range of the data and ensure the normality and rationality of the data.

[0076] In an optional embodiment, a preset data interval can be set according to energy characteristics and industry standards, and then the outlier detection algorithm in the statistical method or machine learning method can be used to determine whether the energy consumption data exceeds the preset data interval. If it exceeds, it does not meet the validity quality standard, and if it does not exceed, it meets the validity quality standard. The above detection process can ensure that the energy consumption data is within a normal and reasonable range, providing accurate and reliable data support for energy consumption calculation, energy analysis and decision-making. At the same time, the data review and correction process is initiated for the detected abnormal data to ensure data quality and prevent abnormal data from affecting the calculation of the target discount coefficient.

[0077] According to another aspect of an embodiment of the present invention, a device for determining energy consumption is also provided. The device can execute the method for determining energy consumption of a mine in the above embodiment. The specific implementation method and preferred application scenario are the same as those in the above embodiment and will not be repeated here.

[0078] Figure 2 1 is a schematic diagram of an energy consumption determination device according to an embodiment of the present invention. As shown in the figure, the device includes: an acquisition module 202, a detection module 204, a determination module 206, and a conversion module 208.

[0079] An acquisition module 202 is used to acquire energy consumption data and energy type of energy; a detection module 204 is used to perform quality detection on energy consumption data to obtain detection results, wherein the detection results are used to indicate whether the energy consumption data meets preset quality standards; a determination module 206 is used to determine a target discount coefficient of energy based on the detection results and energy type, wherein the target discount coefficient is used to indicate a conversion factor for converting energy into standard coal equivalent; a conversion module 208 is used to convert energy consumption data based on the target discount coefficient to obtain energy consumption of energy, wherein the energy consumption is used to indicate the value of energy in standard coal equivalent.

[0080] Optionally, the determination module includes: a first response unit, used to respond to the detection result that the energy consumption data meets the preset quality standard, call the energy discount coefficient calculation model based on the energy type, input the energy consumption data into the discount coefficient calculation model, and obtain the target discount coefficient; a second response unit, used to respond to the detection result that the energy consumption data does not meet the preset quality standard, call the preset discount coefficient of the energy based on the energy type, and determine the preset discount coefficient as the target discount coefficient.

[0081] Optionally, the device also includes: a retrieval module, used to retrieve the preset discount coefficient of energy from the database based on the energy type; an update module, used to update the preset discount coefficient based on the target discount coefficient to obtain an updated preset discount coefficient; and a storage module, used to store the updated preset discount coefficient in the database.

[0082] Optionally, the preset quality standards include at least one of the following: integrity quality standard, timeliness quality standard, effectiveness quality standard, and the detection module includes: a first detection unit, used to perform integrity detection on energy consumption data to obtain an integrity detection result, wherein the integrity detection result is used to indicate whether the energy consumption data meets the integrity quality standard; a second detection unit, used to perform timeliness detection on energy consumption data to obtain a timeliness detection result, wherein the timeliness detection result is used to indicate whether the energy consumption data meets the timeliness quality standard; a third detection unit, used to perform effectiveness detection on energy consumption data to obtain a effectiveness detection result, wherein the effectiveness detection result is used to indicate whether the energy consumption data meets the effectiveness quality standard; a determination unit, used to determine the detection result based on any one or more of the integrity detection result, the timeliness detection result, and the effectiveness detection result.

[0083] Optionally, the first detection unit includes: a first acquisition subunit, used to acquire at least one quality indicator of energy; a first determination subunit, used to determine, in response to the energy consumption data being data corresponding to at least one quality indicator, that the integrity detection result is that the energy consumption data meets the integrity quality standard; and a second determination subunit, used to determine, in response to the energy consumption data not being data corresponding to at least one quality indicator, that the integrity detection result is that the energy consumption data does not meet the integrity quality standard.

[0084] Optionally, the second detection unit includes: a second acquisition subunit, used to acquire the receiving time point of the energy consumption data; a third determination subunit, used to determine that the timeliness detection result is that the energy consumption data meets the timeliness quality standard in response to the receiving time point being in a preset time interval; and a fourth determination subunit, used to determine that the timeliness detection result is that the energy consumption data does not meet the timeliness quality standard in response to the receiving time point not being in the preset time interval.

[0085] Optionally, the third detection unit includes: a third acquisition subunit, used to acquire a preset data interval of energy; a fifth determination subunit, used to determine, in response to the energy consumption data being in the preset data interval, that the validity detection result is that the energy consumption data meets the validity quality standard; and a sixth determination subunit, used to determine, in response to the energy consumption data not being in the preset data interval, that the validity detection result is that the energy consumption data does not meet the validity quality standard.

[0086] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by one or more processors, the one or more processors execute the above-mentioned method for determining energy consumption.

[0087] The storage device in the above steps can be a kind of sequential logic circuit, a memory component used to store data and instructions, etc., mainly used to store programs and data; the processor can be a functional unit that interprets and executes instructions, and it has a unique set of operating commands, which can be called the instruction set of the processor, such as storage, loading, etc. are all operations; the storage device stores computer programs, which can be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0088] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is further provided. The computer-readable storage medium includes a stored program, wherein when the program is executed, the processor of the device where the program is located is controlled to execute the above-mentioned method for determining energy consumption.

[0089] The computer storage medium in the above steps can be a medium used to store certain discontinuous physical quantities in a computer memory, and the computer storage medium mainly includes semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser disks, etc. The stored program included in the computer-readable storage medium can be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0090] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program, and the computer program executes the above-mentioned method for determining energy consumption when being executed by a processor.

[0091] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0094] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0095] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0096] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining energy consumption, characterized in that: include: Obtain energy consumption data and energy types of energy sources; Performing a quality test on the energy consumption data to obtain a test result, wherein the test result is used to indicate whether the energy consumption data meets a preset quality standard; Determine a target conversion factor of the energy based on the detection result and the energy type, wherein the target conversion factor is used to represent a conversion factor for converting the energy into standard coal equivalent; The energy consumption data is converted based on the target conversion coefficient to obtain the energy consumption of the energy, wherein the energy consumption is used to represent the value of the energy in terms of standard coal equivalent.

2. The method for determining energy consumption according to claim 1, characterized in that: Determining a target discount coefficient of the energy source based on the detection result and the energy type includes: In response to the detection result that the energy consumption data meets the preset quality standard, calling the energy discount coefficient calculation model based on the energy type, inputting the energy consumption data into the discount coefficient calculation model, and obtaining the target discount coefficient; In response to the detection result that the energy consumption data does not meet the preset quality standard, a preset discount coefficient of the energy is retrieved based on the energy type, and the preset discount coefficient is determined to be the target discount coefficient.

3. The method for determining energy consumption according to claim 2, characterized in that: After inputting the energy consumption data into the discount coefficient calculation model to obtain the target discount coefficient, the method further includes: Retrieving the preset discount coefficient of the energy from a database based on the energy type; The preset discount coefficient is updated based on the target discount coefficient to obtain an updated preset discount coefficient; The updated preset discount coefficient is stored in the database.

4. The method for determining energy consumption according to claim 1, characterized in that: The preset quality standard includes at least one of the following: integrity quality standard, timeliness quality standard, and effectiveness quality standard. The energy consumption data is quality tested to obtain a test result, including: Performing integrity detection on the energy consumption data to obtain an integrity detection result, wherein the integrity detection result is used to indicate whether the energy consumption data meets the integrity quality standard; Performing a timeliness test on the energy consumption data to obtain a timeliness test result, wherein the timeliness test result is used to indicate whether the energy consumption data meets the timeliness quality standard; Performing validity detection on the energy consumption data to obtain a validity detection result, wherein the validity detection result is used to indicate whether the energy consumption data meets the validity quality standard; The test result is determined based on any one or more of the integrity test result, the timeliness test result, and the validity test result.

5. The method for determining energy consumption according to claim 4, characterized in that: Performing integrity check on the energy consumption data to obtain integrity check results, including: obtaining at least one quality indicator of the energy source; In response to the energy consumption data being data corresponding to the at least one quality indicator, determining that the integrity detection result is that the energy consumption data meets the integrity quality standard; In response to the energy consumption data not being data corresponding to the at least one quality indicator, determining the integrity detection result as the energy consumption data not meeting the integrity quality standard.

6. The method for determining energy consumption according to claim 4, characterized in that: Performing a timeliness test on the energy consumption data to obtain a timeliness test result, including: Obtaining a receiving time point of the energy consumption data; In response to the receiving time point being within a preset time interval, determining the timeliness detection result as that the energy consumption data meets the timeliness quality standard; In response to the receiving time point not being within the preset time interval, determining the timeliness detection result as the energy consumption data not meeting the timeliness quality standard.

7. The method for determining energy consumption according to claim 4, characterized in that: Performing validity detection on the energy consumption data to obtain validity detection results includes: Obtaining a preset data interval of the energy source; In response to the energy consumption data being in the preset data interval, determining the validity detection result as that the energy consumption data meets the validity quality standard; In response to the energy consumption data not being within the preset data interval, determining the validity detection result as the energy consumption data not meeting the validity quality standard.

8. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 7 when running.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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