Smart energy intelligent management method and system based on digital twinning

Abstract

The invention discloses a smart energy intelligent management method and system based on digital twinning, and belongs to the technical field of energy management. The method and the device are used for solving the technical problems of poor autonomous supervision effect and poor autonomous regulation effect of energy management caused by single supervision dimension and single adaptive dynamic adjustment mode of energy management scheme implementation in an existing scheme. Monitoring, counting, processing and analyzing the daily total power supply and daily total power consumption in the target area to obtain a daily power supply reliable identifier and a daily power supply reliable state corresponding to the target area every day; periodically processing and analyzing the daily supply stable state of the target area according to the daily supply reliable supervision sequence obtained through earlier-stage processing, and dynamically managing subsequent implementation of an existing daily supply scheme in a self-adaptive manner according to the stage supply stable state; the implementation effect of the energy supply stage adjustment scheme is traced and evaluated, and the subsequent implementation of the energy supply stage adjustment scheme is dynamically optimized and managed.

Description

Technical Field

[0001] The present invention relates to the field of energy management technology, and in particular to a smart energy intelligent management method and system based on digital twins. Background Art

[0002] Energy management refers to the comprehensive planning, control and supervision of energy production, distribution, conversion and use through a series of technical and management measures to achieve efficient energy utilization, conservation and environmental protection; it covers the entire process from energy procurement, use to waste disposal, aiming to improve energy utilization, reduce energy waste, lower operating costs, and meet environmental protection requirements.

[0003] When implementing the existing intelligent energy management solutions, it is unable to supervise and analyze the energy supply status between the actual daily power supply and actual consumption in the target area, and thus is unable to obtain the local energy supply status and periodic energy supply status corresponding to the existing energy management solutions in the target area. At the same time, it is also unable to use the local energy supply status and periodic energy supply status to adaptively perform daily energy supply dynamic management and stage energy dynamic management. The energy management solution implementation has a single supervision dimension and a single adaptive dynamic adjustment method, resulting in poor autonomous supervision and autonomous regulation effects of energy management. Summary of the invention

[0004] The purpose of the present invention is to provide a smart energy intelligent management method and system based on digital twins, which is used to solve the technical problems of the single supervision dimension and single adaptive dynamic adjustment method of the implementation of energy management solutions in existing solutions, resulting in poor autonomous supervision and autonomous regulation effects of energy management.

[0005] The purpose of the present invention can be achieved through the following technical solutions: Smart energy intelligent management methods based on digital twins include: Monitor, count, process and analyze the daily total power supply and daily total power consumption in the target area, obtain the daily power supply reliability mark and daily power supply reliability status corresponding to the target area, and sort and combine the daily power supply reliability marks obtained by processing the target area every day to obtain the daily power supply reliability supervision sequence; According to the daily power supply reliability supervision sequence, the daily supply stability state of the target area is processed and analyzed to determine the stage supply stability state of the target area, and the subsequent implementation of the existing daily power supply plan of the target area is dynamically evaluated and adjusted according to the analysis results; Among them, the daily power supply reliability supervision sequence is processed and analyzed to obtain the stage supply stability state normal, the stage supply stability state second abnormality or the stage supply stability state third abnormality corresponding to the preset stage supply stability supervision cycle; According to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state, the stage supply stability mark associated with the stage supply stability supervision cycle is processed and calculated and analyzed to determine the abnormality degree corresponding to the stage supply stability supervision cycle; According to the second abnormal severity of the stage supply stability state or the third abnormal severity of the stage supply stability state obtained through the target area analysis, the energy supply stage adjustment plan is implemented for the subsequent target stage supply stability supervision cycle; Conduct retroactive evaluation on the implementation effect of the energy supply stage adjustment plan, determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimize the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect.

[0006] Preferably, the total daily power supply and total daily power consumption of the target area are monitored and counted, and the formula Calculate and obtain the daily power supply reliability value RGi corresponding to the target area every day; where i is a different date, i=1, 2, 3, ..., n; n is a positive integer; DGi and DHi are the daily total power supply and daily total power consumption of the target area respectively; GBi is the standard power supply buffer corresponding to the target area every day; And, input the calculated daily power supply reliability value into the daily power supply reliability identification function for data analysis, and output the daily power supply reliability identifier RBi corresponding to the target area on that day; The daily power supply reliability indicator contains a value of -1, 0 or 1; The daily power supply reliability identifications obtained from the target area are arranged and combined in order of power supply time to obtain the daily power supply reliability supervision sequence.

[0007] Preferably, the expression of the daily power supply reliability identification function is: ; In the formula, B1 and B2 are the minimum and maximum daily power supply buffer corresponding to the power supply of the target area on that day.

[0008] Preferably, the daily power supply reliability indicator of the day in the daily power supply reliability supervision sequence is set as the basic monitoring element, and the elements in the following N rows in the daily power supply reliability supervision sequence are all marked as selected monitoring elements; When processing and analyzing the daily supply stability state corresponding to the target area between the basic monitoring elements and the N selected monitoring elements, the total number of elements with a value of -1 N1, the total number of elements with a value of 0 N2, and the total number of elements with a value of 1 N3 are counted, and the total number of elements with the largest value is obtained and analyzed by comparing the total number of different elements; If the three values ​​are the same, it is indicated that the first abnormality of the stage supply stability state of the target area is detected, and the stage supply stability flag associated with the stage supply stability supervision cycle is set to W1; If the largest value is N2, it indicates that the stage supply stability state of the target area is normal, and the stage supply stability flag associated with the stage supply stability supervision cycle is set to W2.

[0009] Preferably, if the largest value is N1, it indicates that the second abnormality of the stage supply stable state of the target area; If the largest value is N3, it indicates that the target area has a third abnormality in the stage supply stability state; When calculating the stage supply stability flag associated with the stage supply stability supervision cycle according to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state, the largest value N1 or N3 is calculated by the formula Calculate and obtain the corresponding stage supply stability mark WY; where NM is the largest value N1 or N3; NZ is the total number of basic monitoring elements and selected monitoring elements; α is the error correction factor, which is calculated by The formula is used to calculate the maximum value of the total number of consecutive -1 values ​​or the total number of consecutive 1 values. The calculated stage supply stability identifier is processed and analyzed to determine the degree of abnormality corresponding to the stage supply stability supervision cycle.

[0010] Preferably, the abnormality degree value CY corresponding to the second abnormality of the stage supply stable state or the third abnormality of the stage supply stable state is calculated by the formula CY=[WY / BJ]; wherein BJ is the standard value of the stage supply stable abnormality; [*] is a rounding function, indicating obtaining the maximum integer not exceeding the real number *; If the abnormality level value is 0, it indicates that the second abnormality of the stage supply stable state of the target area is slight or the third abnormality of the stage supply stable state is slight; If the abnormality level value is not 0, it will prompt the target area's stage supply stability state second abnormality severity or stage supply stability state third abnormality severity, and at the same time, the energy supply stage adjustment plan will be implemented for the subsequent target stage supply stability supervision cycle.

[0011] Preferably, when the energy supply stage adjustment plan is implemented, the daily power supply total DGi' corresponding to different dates in the target stage supply stability supervision cycle is obtained, and the daily power supply totals on different dates are successively calculated through the formula Calculate and obtain the corresponding daily power supply adjustment amount DTi´; where i´ is the different dates in the target phase supply stability supervision cycle, i´=1, 2, 3, ..., N+1; GBi´ is the standard power supply buffer amount on different dates in the target phase supply stability supervision cycle corresponding to the target area; The daily power supply adjustment amount obtained by processing on different dates is used to provide daily power supply to the target area within the target stage supply stability supervision cycle.

[0012] Preferably, the target day power supply reliability supervision sequence corresponding to the M target stage supply stability supervision cycles after the implementation of the energy supply stage adjustment plan is obtained, and data analysis is performed on different target day power supply reliability supervision sequences in turn to obtain the corresponding target stage supply stability identifier, and the first supervision total number NJ1 with the stage supply stability identifier set to W1 and the second supervision total number NJ2 with the stage supply stability identifier set to W2 are counted, and the first supervision total number and the second supervision total number are calculated by the formula Calculate and obtain the adjustment implementation validity SX corresponding to the adjustment plan in the energy supply stage; where β is the error compensation coefficient, and its value range is (0, 1); BT is the standard value of the adjustment implementation validity corresponding to the adjustment plan in the energy supply stage.

[0013] Preferably, data analysis is performed on the calculated adjustment implementation validity to determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamic optimization management is performed on the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect; If the adjustment implementation validity is greater than or equal to 1, then an adjustment implementation effective instruction is generated and the energy supply stage adjustment plan is controlled to be implemented subsequently; If the adjustment implementation validity is less than 1, an invalid adjustment implementation instruction is generated and the energy supply stage adjustment plan is controlled to be subsequently optimized and adjusted.

[0014] Smart energy intelligent management system based on digital twin, including: The daily energy supply supervision processing module is used to monitor, count, process and analyze the daily total power supply and daily power consumption in the target area, obtain the daily power supply reliability mark and daily power supply reliability status corresponding to the target area, and sort and combine the daily power supply reliability marks obtained by daily processing in the target area to obtain the daily power supply reliability supervision sequence; The phase energy supply evaluation management module is used to process and analyze the daily supply stability state of the target area according to the daily power supply reliability supervision sequence, determine the phase supply stability state of the target area, and dynamically evaluate and adjust the subsequent implementation of the existing daily power supply plan of the target area according to the analysis results; The energy supply management evaluation and optimization module is used to conduct retrospective evaluation on the implementation effect of the energy supply stage adjustment plan, determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimize the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect.

[0015] Compared with the existing solutions, the present invention achieves the following beneficial effects: The present invention obtains the daily power supply reliability mark and daily power supply reliability status corresponding to the target area every day by monitoring, counting, processing and analyzing the daily total power supply and daily power consumption in the target area, and realizes the digital processing and representation of the daily power supply reliability status of the target area every day. It can not only obtain the daily power supply reliability status of the target area, but also provide reliable data support for the subsequent multi-dimensional supervision and analysis of the stable supply status of the target area.

[0016] The present invention periodically processes and analyzes the daily supply stability state of the target area through the daily power supply reliable supervision sequence obtained through preliminary processing, determines the stage supply stability state of the target area, and adaptively and dynamically manages the subsequent implementation of the existing daily power supply plan according to the stage supply stability state, so that the total daily power supply in the target area can meet the electricity demand of users without causing a large waste of excess power supply, thereby improving the autonomous supervision effect and autonomous optimization and adjustment effect of the existing energy supply plan.

[0017] The present invention determines the adjustment implementation effect corresponding to the energy supply stage adjustment plan by retroactively evaluating the implementation effect of the energy supply stage adjustment plan, and dynamically optimizes the subsequent implementation of the energy supply stage adjustment plan according to the adjustment implementation effect, thereby realizing autonomous supervision analysis and re-optimization management of the implementation effect of the energy supply stage adjustment plan after autonomous optimization management in the early stage, thereby improving the autonomous re-regulation and supervision effect of the implementation of the energy management plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below in conjunction with the accompanying drawings.

[0019] Figure 1 This is a flowchart of the smart energy intelligent management method based on digital twins of the present invention.

[0020] Figure 2 This is a flowchart of the steps for processing and analyzing the daily supply stability state corresponding to the target area in the present invention.

[0021] Figure 3 A flowchart of the steps for dynamically optimizing the subsequent implementation of the energy supply phase adjustment plan in the present invention.

[0022] Figure 4 This is a module block diagram of the smart energy intelligent management system based on digital twins in the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 are within the scope of protection of the present invention.

[0024] Example 1: Figure 1 As shown, the present invention is a smart energy intelligent management method based on digital twins, comprising: The daily total power supply and daily total power consumption in the target area are monitored, counted, processed and analyzed to obtain the daily power supply reliability mark and daily power supply reliability status corresponding to the target area, and the daily power supply reliability marks obtained by processing the target area daily are sorted and combined to obtain the daily power supply reliability supervision sequence; the specific steps include: Monitor and count the total daily power supply and daily power consumption in the target area, and calculate the total daily power consumption through the formula Calculate and obtain the daily power supply reliability value RGi corresponding to the target area every day; where i is a different date, i=1, 2, 3, ..., n; n is a positive integer; DGi and DHi are the daily total power supply and daily total power consumption of the target area respectively; GBi is the daily standard power supply buffer corresponding to the target area, which can be determined based on the existing daily power supply operation requirement data; It should be noted that the target area can be specifically determined according to the actual application scenario, such as an administrative area; In addition, the total daily power supply of the target area can be obtained based on the historical daily power consumption data of the target area combined with digital twin technology and the existing power consumption forecasting scheme. The specific steps are not repeated here; And, input the calculated daily power supply reliability value into the daily power supply reliability identification function for data analysis, and output the daily power supply reliability identifier RBi corresponding to the target area on that day; Among them, the expression of daily power supply reliability identification function is: ; Wherein, B1 and B2 are the minimum and maximum daily power supply buffer corresponding to the power supply of the target area on that day, respectively, which can be determined according to the standard power supply buffer corresponding to the target area on a daily basis and the preset minimum and maximum requirement data; The daily power supply reliability indicator contains a value of -1, 0 or 1; It should be noted that by calculating the daily total power supply and daily total power consumption, the daily power supply reliability status of the target area can be digitally represented; at the same time, it can provide reliable daily power supply reliability status supervision data support for the subsequent multi-dimensional supervision analysis of the implementation of the energy management plan.

[0025] A daily power supply reliability indicator with a value of -1 indicates that the daily power supply reliability status of the target area on that day is a poor daily power supply buffer status, that is, the difference between the daily power supply and the daily power consumption on that day does not meet the minimum requirement of the standard power supply buffer; The daily power supply reliability indicator with a value of 0 indicates that the daily power supply reliability status of the target area corresponding to that day is the daily power supply buffer normal status; The daily power supply reliability indicator with a value of 1 indicates that the daily power supply reliability state corresponding to the target on that day is the daily power supply buffer excess state; that is, the difference between the daily power supply total amount and the daily power consumption total amount on that day exceeds the maximum requirement of the standard power supply buffer amount; The daily power supply reliability marks obtained by processing the target area every day are arranged and combined in the order of power supply time to obtain the daily power supply reliability supervision sequence; In the embodiment of the present invention, by monitoring, counting, processing and analyzing the daily total power supply and daily total power consumption in the target area, the daily power supply reliability mark and daily power supply reliability status corresponding to the target area are obtained, and the daily power supply reliability status of the target area is digitized and represented. The daily power supply reliability status of the target area can be obtained, and reliable data support can be provided for the subsequent multi-dimensional supervision and analysis of the stable supply status of the target area.

[0026] According to the daily power supply reliability supervision sequence, the daily supply stability state of the target area is processed and analyzed, the stage supply stability state of the target area is determined, and the subsequent implementation of the existing daily power supply plan of the target area is dynamically evaluated and adjusted according to the analysis results; the specific steps include: The daily power supply reliability flag of the day in the daily power supply reliability supervision sequence is set as the basic monitoring element, and the elements in the following N rows in the daily power supply reliability supervision sequence are all marked as selected monitoring elements; N is a positive integer and an even number, specifically 6; When processing and analyzing the daily supply stability state corresponding to the target area between the basic monitoring elements and the N selected monitoring elements, the total number of elements with a value of -1 N1, the total number of elements with a value of 0 N2, and the total number of elements with a value of 1 N3 are counted, and the total number of elements with the largest value is obtained and analyzed by comparing the total number of different elements; this can also be implemented according to the max{} function to obtain the maximum value among several real numbers; like Figure 2 As shown, if the three values ​​are the same, it indicates that the first abnormality of the stage supply stability state of the target area is indicated, and the stage supply stability flag associated with the stage supply stability supervision cycle is set to W1; the first abnormality indicates that the daily power supply buffer state is poor, the daily power supply buffer state is normal, and the daily power supply buffer state is excessive; If the largest value is N2, it indicates that the stage supply stability state of the target area is normal, and the stage supply stability flag associated with the stage supply stability supervision cycle is set to W2; If the largest value is N1, it indicates that the target area has a second abnormality in the stage supply stability state; If the largest value is N3, it indicates that the target area has a third abnormality in the stage supply stability state; Among them, the second anomaly indicates that the stage power supply reliability state of the target area corresponding to the stage supply stability supervision cycle is the stage power supply buffering poor state; The third anomaly indicates that the stage power supply reliability state of the target area corresponding to the stage supply stability supervision cycle is the stage power supply buffer excess state; When calculating the stage supply stability flag associated with the stage supply stability supervision cycle according to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state, the largest value N1 or N3 is calculated by the formula Calculate and obtain the corresponding stage supply stability mark WY; where NM is the largest value N1 or N3; NZ is the total number of basic monitoring elements and selected monitoring elements; α is the error correction factor, which is calculated by The formula is used to calculate the maximum value of the total number of consecutive -1 values ​​or the total number of consecutive 1 values. It should be noted that the stage supply stability identifier is used to calculate the stage supply stability abnormality data corresponding to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state, so as to digitally represent the stage supply stability abnormality state corresponding to the stage supply stability supervision cycle; Process and analyze the calculated stage supply stability identifier to determine the abnormality level corresponding to the stage supply stability supervision cycle; The abnormality degree value CY corresponding to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state is calculated by the formula CY=[WY / BJ]; where BJ is the standard value of the stage supply stability abnormality, which is determined according to the actual stage power supply design requirement data of the actual application scenario, and can also be determined according to the test data of the same several stage supply stability supervision cycles in the previous period; [*] is the rounding function, which means obtaining the maximum integer that does not exceed the real number *; If the abnormality level value is 0, it indicates that the second abnormality of the stage supply stability state of the target area is slight or the third abnormality of the stage supply stability state is slight, and at the same time, the implementation of the existing daily power supply plan is maintained for the subsequent target stage supply stability supervision cycle; If the abnormality level value is not 0, the target area will be prompted with the second abnormal severity of the stage supply stability state or the third abnormal severity of the stage supply stability state, and the energy supply stage adjustment plan will be implemented for the subsequent target stage supply stability supervision cycle; In the embodiment of the present invention, the daily power supply reliability supervision sequence obtained by the previous processing is expanded through a preset stage supply stability supervision cycle to perform data analysis on the stage supply stability state corresponding to the target area, and the subsequent implementation of the existing daily power supply plan in the target area is dynamically evaluated and adjusted according to the analysis results, thereby improving the supervision diversity and comprehensiveness of the implementation of the energy management plan.

[0027] The implementation of the supply stability supervision cycle in the target phase is to re-mark the basic monitoring elements and the elements in the middle of the N selected monitoring elements as basic monitoring elements, and re-mark the N elements following the re-marked basic monitoring elements as selected monitoring elements; In addition, when the energy supply stage adjustment plan is implemented, the daily power supply total DGi´ corresponding to different dates in the target stage supply stability supervision cycle is obtained, and the daily power supply totals on different dates are successively calculated through the formula Calculate and obtain the corresponding daily power supply adjustment amount DTi´; where i´ is the different dates in the target phase supply stability supervision cycle, i´=1, 2, 3, ..., N+1; GBi´ is the standard power supply buffer amount on different dates in the target phase supply stability supervision cycle corresponding to the target area, which can be the same as the value of GBi; According to the daily power supply adjustment amount obtained by processing on different dates, the target area is provided with daily power supply within the target stage supply stability supervision cycle; In the embodiment of the present invention, the daily power supply reliable supervision sequence obtained by the previous processing is used to periodically process and analyze the daily supply stability state of the target area to determine the stage supply stability state of the target area. At the same time, the subsequent implementation of the existing daily power supply plan is adaptively managed dynamically according to the stage supply stability state, so that the total daily power supply in the target area can meet the electricity demand of users without causing a large amount of excess power supply waste, thereby improving the autonomous supervision effect and autonomous optimization and adjustment effect of the existing energy supply plan.

[0028] Conduct retrospective evaluation on the implementation effect of the energy supply stage adjustment plan, determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimize the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect; the specific steps include: It should be noted that by retrospectively evaluating the implementation effect of the energy supply stage adjustment plan, the subsequent implementation of the energy supply stage adjustment plan can be dynamically optimized and managed, thereby improving the diversity and reliability of energy management.

[0029] Obtain the target day power supply reliability supervision sequence corresponding to the M target stage supply stability supervision cycles after the implementation of the energy supply stage adjustment plan, where M is a positive integer, specifically 10, and perform data analysis on different target day power supply reliability supervision sequences in turn to obtain the corresponding target stage supply stability identification. The target stage supply stability identification is the same as the processing technical solution for the previous stage supply stability identification, which will not be repeated here. The first supervision total number NJ1 with the stage supply stability identification set to W1 and the second supervision total number NJ2 with the stage supply stability identification set to W2 are counted, and the first supervision total number and the second supervision total number are calculated by the formula Calculate and obtain the adjustment implementation validity SX corresponding to the energy supply stage adjustment plan; where β is the error compensation coefficient, and the value range is (0, 1), specifically 0.75; BT is the adjustment implementation validity standard value corresponding to the energy supply stage adjustment plan, which can be determined based on the design requirement data of the energy supply stage adjustment plan, or based on the test data of the previous supply stability supervision cycle of the same several stages; It should be noted that the adjustment implementation validity is used to calculate different implementation effect data corresponding to the energy supply stage adjustment plan, so as to digitally represent the adjustment implementation effect corresponding to the energy supply stage adjustment plan; like Figure 3 As shown, the calculated adjustment implementation validity is analyzed to determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and the subsequent implementation of the energy supply stage adjustment plan is dynamically optimized and managed according to the adjustment implementation effect; If the adjustment implementation validity is greater than or equal to 1, then an adjustment implementation effective instruction is generated and the energy supply stage adjustment plan is controlled to be implemented subsequently; If the adjustment implementation validity is less than 1, an invalid adjustment implementation instruction is generated and the energy supply stage adjustment plan is controlled to be subsequently optimized and adjusted.

[0030] Among them, the subsequent optimization and adjustment of the energy supply stage adjustment plan can be determined according to the alternative plan corresponding to the design of the energy supply stage adjustment plan, or customized by professional and technical personnel in this field according to the actual application requirements of the actual application scenario.

[0031] In the embodiment of the present invention, by retroactively evaluating the implementation effect of the energy supply stage adjustment plan, determining the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimizing the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect, autonomous supervision analysis and re-optimization management of the implementation effect of the energy supply stage adjustment plan after autonomous optimization management are achieved, thereby improving the autonomous re-regulation and supervision effect of the implementation of the energy management plan.

[0032] Example 2: Figure 4 As shown in the figure, the smart energy intelligent management system based on digital twin includes: The daily energy supply supervision processing module is used to monitor, count, process and analyze the daily total power supply and daily power consumption in the target area, obtain the daily power supply reliability mark and daily power supply reliability status corresponding to the target area, and sort and combine the daily power supply reliability marks obtained by daily processing in the target area to obtain the daily power supply reliability supervision sequence; The phase energy supply evaluation management module is used to process and analyze the daily supply stability state of the target area according to the daily power supply reliability supervision sequence, determine the phase supply stability state of the target area, and dynamically evaluate and adjust the subsequent implementation of the existing daily power supply plan of the target area according to the analysis results; The energy supply management evaluation and optimization module is used to conduct retrospective evaluation on the implementation effect of the energy supply stage adjustment plan, determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimize the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect.

[0033] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0034] In the several embodiments provided by the present invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0035] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0036] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0037] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0038] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. Intelligent energy management method based on digital twins, It is characterized in that include: Monitor, count, process and analyze the daily total power supply and daily total power consumption in the target area, obtain the daily power supply reliability mark and daily power supply reliability status corresponding to the target area, and sort and combine the daily power supply reliability marks obtained by processing the target area every day to obtain the daily power supply reliability supervision sequence; According to the daily power supply reliability supervision sequence, the daily supply stability state of the target area is processed and analyzed to determine the stage supply stability state of the target area, and the subsequent implementation of the existing daily power supply plan of the target area is dynamically evaluated and adjusted according to the analysis results; Among them, the daily power supply reliability supervision sequence is processed and analyzed to obtain the stage supply stability state normal, the stage supply stability state second abnormality or the stage supply stability state third abnormality corresponding to the preset stage supply stability supervision cycle; According to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state, the stage supply stability mark associated with the stage supply stability supervision cycle is processed and calculated and analyzed to determine the abnormality degree corresponding to the stage supply stability supervision cycle; According to the second abnormal severity of the stage supply stability state or the third abnormal severity of the stage supply stability state obtained through the target area analysis, the energy supply stage adjustment plan is implemented for the subsequent target stage supply stability supervision cycle; Conduct retroactive evaluation on the implementation effect of the energy supply stage adjustment plan, determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimize the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect.

2. According to the smart energy intelligent management method based on digital twins according to claim 1, It is characterized in that Monitor and count the total daily power supply and daily power consumption in the target area, and calculate the total daily power consumption through the formula Calculate and obtain the daily power supply reliability value RGi corresponding to each day in the target area; where i is a different date, i=1, 2, 3, ..., n; n is a positive integer; DGi and DHi are the daily power supply and daily power consumption of the target area respectively; GBi is the standard daily power supply buffer corresponding to the target area; And, input the calculated daily power supply reliability value into the daily power supply reliability identification function for data analysis, and output the daily power supply reliability identifier RBi corresponding to the target area on that day; The daily power supply reliability indicator contains a value of -1, 0 or 1; The daily power supply reliability identifications obtained from the target area are arranged and combined in order of power supply time to obtain the daily power supply reliability supervision sequence.

3. According to the smart energy intelligent management method based on digital twins according to claim 2, It is characterized in that The expression of daily power supply reliability identification function is: ; In the formula, B1 and B2 are the minimum and maximum daily power supply buffer corresponding to the power supply of the target area on that day.

4. According to the smart energy intelligent management method based on digital twins according to claim 2, It is characterized in that The daily power supply reliability indicator of the current day in the daily power supply reliability supervision sequence is set as the basic monitoring element, and the elements in the following N rows in the daily power supply reliability supervision sequence are all marked as selected monitoring elements; When processing and analyzing the daily supply stability state corresponding to the target area between the basic monitoring elements and the N selected monitoring elements, the total number of elements with a value of -1 N1, the total number of elements with a value of 0 N2, and the total number of elements with a value of 1 N3 are counted, and the total number of elements with the largest value is obtained and analyzed by comparing the total number of different elements; If the three values ​​are the same, it is indicated that the first abnormality of the stage supply stability state of the target area is detected, and the stage supply stability flag associated with the stage supply stability supervision cycle is set to W1; If the largest value is N2, it indicates that the stage supply stability state of the target area is normal, and the stage supply stability flag associated with the stage supply stability supervision cycle is set to W2.

5. According to the smart energy intelligent management method based on digital twins according to claim 4, It is characterized in that If the largest value is N1, it indicates that the target area has a second abnormality in the stage supply stability state; If the largest value is N3, it indicates that the target area has a third abnormality in the stage supply stability state; When calculating the stage supply stability flag associated with the stage supply stability supervision cycle according to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state, the largest value N1 or N3 is calculated by the formula Calculate and obtain the corresponding stage supply stability mark WY; where NM is the largest value N1 or N3; NZ is the total number of basic monitoring elements and selected monitoring elements; α is the error correction factor, which is calculated by The formula is used to calculate the maximum value of the total number of consecutive -1 values ​​or the total number of consecutive 1 values. The calculated stage supply stability identifier is processed and analyzed to determine the degree of abnormality corresponding to the stage supply stability supervision cycle.

6. According to the smart energy intelligent management method based on digital twins according to claim 5, It is characterized in that The abnormality degree value CY corresponding to the second abnormality of the stage supply stability state or the third abnormality of the stage supply stability state is calculated by the formula CY=[WY / BJ]; where BJ is the standard value of the stage supply stability abnormality; [*] is the rounding function, which means obtaining the maximum integer that does not exceed the real number *; If the abnormality level value is 0, it indicates that the second abnormality of the stage supply stable state of the target area is slight or the third abnormality of the stage supply stable state is slight; If the abnormality level value is not 0, it will prompt the target area's stage supply stability state second abnormality severity or stage supply stability state third abnormality severity, and at the same time, the energy supply stage adjustment plan will be implemented for the subsequent target stage supply stability supervision cycle.

7. According to the smart energy intelligent management method based on digital twins according to claim 6, It is characterized in that When the energy supply stage adjustment plan is implemented, the daily power supply total DGi´ corresponding to different dates in the target stage supply stability supervision cycle is obtained, and the daily power supply totals on different dates are calculated in turn through the formula Calculate and obtain the corresponding daily power supply adjustment amount DTi´; where i´ is the different dates in the target phase supply stability supervision cycle, i´=1, 2, 3, ..., N+1; GBi´ is the standard power supply buffer amount on different dates in the target phase supply stability supervision cycle corresponding to the target area; The daily power supply adjustment amount obtained by processing on different dates is used to provide daily power supply to the target area within the target stage supply stability supervision cycle.

8. According to the smart energy intelligent management method based on digital twins according to claim 7, It is characterized in that Obtain the target day power supply reliability supervision sequence corresponding to the M target stage supply stability supervision cycles after the implementation of the energy supply stage adjustment plan, and perform data analysis on different target day power supply reliability supervision sequences in turn to obtain the corresponding target stage supply stability identifier, and count the first supervision total NJ1 with the stage supply stability identifier set to W1 and the second supervision total NJ2 with the stage supply stability identifier set to W2, and add the first supervision total and the second supervision total through the formula Calculate and obtain the adjustment implementation validity SX corresponding to the adjustment plan in the energy supply stage; where β is the error compensation coefficient, and its value range is (0, 1); BT is the standard value of the adjustment implementation validity corresponding to the adjustment plan in the energy supply stage.

9. According to the smart energy intelligent management method based on digital twins according to claim 7, It is characterized in that Conduct data analysis on the calculated adjustment implementation validity to determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimize the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect; If the adjustment implementation validity is greater than or equal to 1, then an adjustment implementation effective instruction is generated and the energy supply stage adjustment plan is controlled to be implemented subsequently; If the adjustment implementation validity is less than 1, an invalid adjustment implementation instruction is generated and the energy supply stage adjustment plan is controlled to be subsequently optimized and adjusted.

10. A smart energy intelligent management system based on digital twins, applying the smart energy intelligent management method based on digital twins as described in any one of claims 1 to 9, It is characterized in that include: The daily energy supply supervision processing module is used to monitor, count, process and analyze the daily total power supply and daily power consumption in the target area, obtain the daily power supply reliability mark and daily power supply reliability status corresponding to the target area, and sort and combine the daily power supply reliability marks obtained by daily processing in the target area to obtain the daily power supply reliability supervision sequence; The phase energy supply evaluation management module is used to process and analyze the daily supply stability state of the target area according to the daily power supply reliability supervision sequence, determine the phase supply stability state of the target area, and dynamically evaluate and adjust the subsequent implementation of the existing daily power supply plan of the target area according to the analysis results; The energy supply management evaluation and optimization module is used to conduct retrospective evaluation on the implementation effect of the energy supply stage adjustment plan, determine the adjustment implementation effect corresponding to the energy supply stage adjustment plan, and dynamically optimize the subsequent implementation of the energy supply stage adjustment plan based on the adjustment implementation effect.

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