Smart energy comprehensive regulation and control method, device and equipment and storage medium

Abstract

The invention relates to the technical field of energy supervision, in particular to a smart energy comprehensive regulation and control method, device and equipment and a storage medium, and the method comprises the steps: obtaining production data, and building a digital twin model based on the production data; obtaining total energy consumption data and effective energy consumption data based on the digital twin model; calculating current energy utilization efficiency based on the total energy consumption data and the effective energy consumption data; judging whether the current energy utilization efficiency accords with a first preset threshold value or not; and if the current energy utilization efficiency does not accord with the first preset threshold value, obtaining an adjustment strategy based on the current energy utilization efficiency. The intelligent energy consumption monitoring system has the effects of automatically monitoring energy consumption and carrying out intelligent processing.

Description

Technical Field

[0001] The present application relates to the technical field of energy supervision, and in particular, to a method, device, equipment and storage medium for comprehensive regulation and control of intelligent energy. Background Art

[0002] In the process of industrial production and operation, the efficient utilization of energy is a key factor for enterprises to achieve cost savings, environmental protection and sustainable development. Traditional energy management methods often rely on manual monitoring and regular evaluation. This method is not only time-consuming and laborious, but also difficult to accurately reflect the actual situation of energy utilization in a timely manner, resulting in prominent problems of energy waste and low efficiency.

[0003] Therefore, how to automatically monitor energy consumption and perform intelligent processing has become an urgent problem to be solved. Summary of the Invention

[0004] In order to automatically monitor energy consumption and perform intelligent processing, the present application provides a method, device, equipment and storage medium for comprehensive regulation and control of intelligent energy.

[0005] In a first aspect, a method for comprehensive regulation and control of intelligent energy provided by the present application adopts the following technical solution: A method for comprehensive regulation and control of intelligent energy, comprising: Obtaining production data and establishing a digital twin model based on the production data; Obtaining total energy consumption data and effective energy consumption data based on the digital twin model; Calculating the current energy utilization efficiency based on the total energy consumption data and the effective energy consumption data; Judging whether the current energy utilization efficiency meets a first preset threshold; If the current energy utilization efficiency does not meet the first preset threshold, obtaining an adjustment strategy based on the current energy utilization efficiency.

[0006] By adopting the above technical solutions, obtaining production data and establishing a digital twin model can achieve an accurate simulation of the actual production process. As a virtual mapping, the digital twin model can reflect various variables and parameters in the production process, providing a solid foundation for subsequent energy data processing. Based on the digital twin model, it is convenient to obtain the total energy consumption data and effective energy consumption data, calculate the current energy utilization efficiency, and compare it with the preset first threshold, enabling rapid identification of whether there are problems in energy utilization. An efficient energy management method helps enterprises promptly adjust strategies and optimize energy use. When the current energy utilization efficiency does not meet the preset threshold, the electronic device can automatically generate an adjustment strategy based on the current energy utilization efficiency. The formulation of an intelligent adjustment strategy avoids the cumbersome and subjective nature of manual intervention, improving the accuracy and timeliness of adjustment. Moreover, it can continuously monitor production data, facilitating users to understand the production situation.

[0007] This precise simulation helps to detect potential energy waste problems in advance, thereby taking preventive measures to avoid unnecessary energy consumption.

[0008] Optionally, the adjustment strategy includes: Judging whether there is an abnormal energy consumption position based on the digital twin model; If there is the abnormal energy consumption position, obtaining the corresponding current product data based on the abnormal energy consumption position; Obtaining the corresponding historical product data based on the abnormal energy consumption position; Judging whether the current product data is abnormal based on the historical product data; If the current product data is normal, obtaining the corresponding first production equipment based on the abnormal energy consumption position; Outputting a maintenance signal and a production reduction signal based on the first production equipment; If the current product data is abnormal, outputting a stop working signal based on the first production equipment.

[0009] By adopting the above technical solution, using the digital twin model, it is possible to monitor the energy consumption situation in real time and accurately locate the position where the energy consumption is abnormal, avoiding the cumbersome process of manual checking one by one, and greatly improving the efficiency and accuracy of problem discovery. After locating the abnormal position of energy consumption, further obtain the current product data and compare it with the historical product data. Through automatic comparison, it is possible to quickly determine whether there is an abnormality in the current product data. According to the abnormality of the current product data, the electronic device can automatically output corresponding signals. If there is no abnormality in the current product data, it is determined that there is a certain problem with the first production device, resulting in a certain increase in energy loss while ensuring production, so the energy utilization rate is reduced. Therefore, at this time, a maintenance signal and a production reduction signal are output to prompt the maintenance of the first production device and appropriately reduce the production volume to prevent possible energy waste problems, and reducing the production volume of the first production device can also reduce the possibility of the abnormality intensifying to a certain extent, playing a role in protecting the first production device. If the current product data is abnormal, a stop working signal is directly output because the situation of abnormal product data has occurred at this time, so it is determined that the situation is relatively serious, and the stop working signal is output to ensure that the problem device will not continue to operate and cause greater energy waste or equipment damage. Through real-time monitoring and intelligent judgment, the refined management of the production process and equipment is realized, avoiding unnecessary energy waste, and at the same time protecting the production equipment and reducing the possibility of equipment damage resulting in inability to produce.

[0010] Optionally, before outputting the stop working signal based on the first production device, it further includes: Obtaining the operation instruction received based on the first production device; Obtaining the production status of the first production device before receiving the operation instruction; Judging whether the operation instruction meets the operation requirements based on the production status; If the operation instruction does not meet the operation requirements, obtain the first preset delay; Within the first preset delay, judge whether the first production device receives a debugging instruction; If the first production device receives the debugging instruction, do not execute the step of outputting the stop working signal based on the first production device.

[0011] If the operation instruction meets the preset requirements, execute the step of outputting the stop working signal based on the first production device.

[0012] By adopting the above technical solution, obtaining the operation instructions received by the first production device, and judging whether the operation instructions meet the operation requirements based on its production status, it is possible to effectively avoid production anomalies caused by misoperations or incorrect instructions, which may further lead to abnormal product data. When the operation instructions do not meet the preset requirements, the electronic device does not immediately perform a shutdown operation but first obtains a preset delay. During this delay period, if it is determined that the production device has received a debugging instruction, it indicates that the operation instructions may be being corrected or the device is undergoing necessary debugging. At this time, the electronic device does not output a stop working signal, thus avoiding unnecessary shutdowns, reducing production interruptions and energy waste. The optimization of the strategy helps to reduce the number of shutdowns and the shutdown time of the production line, improve the utilization rate of the equipment and production efficiency, and the intelligent processing method helps to improve the automation level and response speed of the system.

[0013] Optionally, the method further includes: Obtaining all historical energy utilization rates; Performing trend prediction based on the historical energy utilization to obtain a prediction result; Correcting the first preset threshold based on the prediction result to obtain a correction value; Assigning the correction value to the first preset threshold.

[0014] By adopting the above technical solution, obtaining and analyzing all historical energy utilization rate data, the electronic device can perform trend prediction and gain insights into potential changes in energy utilization efficiency in advance. Correcting the first preset threshold based on the prediction result means that the standard of energy utilization efficiency is dynamically adjusted rather than fixed. This dynamic adjustment mechanism can better adapt to changes in the production environment. The dynamically adjusted first preset threshold can more accurately reflect the energy utilization situation in actual production and can be more accurate in abnormal determination, that is, ensuring the timeliness and effectiveness of the energy management strategy. Based on effective determination processing, it can better help users make improvements to achieve energy conservation, emission reduction and sustainable development, and at the same time can also reduce production costs to a certain extent and increase production benefits.

[0015] Optionally, the performing trend prediction based on the historical energy utilization rate to obtain a prediction result includes: The calculation formula for the prediction result is: ; where k is the time point, that is, each historical energy utilization rate corresponds to a time point; is the prediction result at the k + 1 time point; is the original data sequence the first value of, that is is the value of the first historical energy utilization rate; a and b are known numbers.

[0016] By adopting the above technical solution and calculating using the calculation formula, the energy utilization rate at a certain future time point can be predicted relatively accurately. This prediction ability provides an enterprise with a forward-looking management perspective, helping to plan energy allocation in advance and adjust production strategies. The above calculation formula has relatively low requirements for the integrity and distribution characteristics of data, and can make predictions under the condition of less data or uncertain data distribution, which makes it have strong adaptability and flexibility in practical applications. Users can timely understand the changing trend of the future energy utilization rate, and thus adjust the production situation according to the prediction results. Moreover, by correcting the first preset threshold based on the accurate prediction results, a more accurate result for determining anomalies can also be obtained.

[0017] Optionally, the method further includes: Constructing an original data sequence from historical energy utilization rates ; Accumulating the original data sequence to obtain a new sequence ; Based on the sequence constructing an adjacent mean generation sequence , sequence ; Constructing a data matrix B and a vector Y; Based on the calculation formula: calculating to obtain a parameter vector U; The calculation formula of the parameter vector U is: ; Based on the parameter vector U, the known numbers a and b can be extracted; where represents the kth historical energy utilization rate; represents the cumulative value of the historical energy utilization rates from the first to the kth; the data matrix B is a matrix of , n is the length of the original data sequence, that is, n is the number of historical energy utilization rates, the first column of the data matrix B is all , the second column of the data matrix B is all 1; the vector Y is a vector of dimensions, the vector Y includes the values of the second element to the last element of the original data sequence ; is the transpose matrix of B, is the inverse matrix of.

[0018] By adopting the above technical solution, the original data sequence is constructed, which effectively weakens the randomness and volatility in the original data, making the development trend of the data sequence more obvious and providing a more stable data basis for subsequent modeling. The adjacent mean generation sequence is constructed, and the calculation of the parameter vector U based on this sequence, the data matrix B, and the vector Y ensures that the potential laws in the data sequence can be accurately captured, so as to make accurate predictions. The calculation of the parameter vector U adopts the least square principle, ensuring the stability and accuracy of parameter solution. Through the operations of the transposed matrix and the inverse matrix, the numerical instability problem in the calculation process is effectively avoided. Thus, accurate known numbers a and b can be finally extracted, and further the final prediction result is made more accurate.

[0019] Optionally, before correcting the first preset threshold based on the prediction result to obtain a correction value, it further includes: Obtain the activity log; Judge whether the activity log includes improvement data; If the activity log includes improvement data, obtain the corresponding second evaluation value based on the improvement data; Obtain the first evaluation value before improvement based on the activity log; Calculate the change rate based on the first evaluation value and the second evaluation value; Judge whether the change rate is greater than the second preset threshold; If the change rate is greater than the second preset threshold, do not perform the step of correcting the first preset threshold based on the prediction result to obtain a correction value; If the change rate is not greater than the second preset threshold, perform the step of correcting the first preset threshold based on the prediction result to obtain a correction value.

[0020] By adopting the above technical solutions, obtaining activity logs and analyzing whether they contain improvement data, users can understand whether there are changes in factors affecting energy utilization efficiency. Such changes may stem from the optimization of production processes, the introduction of new technologies, or the adjustment of the external environment, etc. Based on these improvement data, the electronic device can obtain the corresponding second evaluation value and compare it with the first evaluation value before the improvement, so as to calculate the change rate. This ensures that when the electronic device decides whether to correct the first preset threshold, it can fully consider the latest dynamics in actual production and improve the accuracy of the decision-making. When the change rate is greater than the second preset threshold, it means that the energy utilization efficiency has been significantly affected. At this time, directly correcting the first preset threshold based on the prediction result may not be appropriate. Therefore, suspending the correction step can avoid potential risks caused by blind adjustment. And since general improvements can increase energy utilization efficiency, while in the case of no improvement, the energy utilization efficiency decreases. So if adjusted blindly, it may lead to an inaccurate determination of the energy utilization efficiency after improvement. When the change rate is not greater than the second preset threshold, the electronic device will continue to execute the step of correcting the first preset threshold based on the prediction result to ensure that the energy management strategy can keep up with the changes in the production environment. This flexibility helps users better cope with various uncertainties and maintain the effectiveness and efficiency of energy management.

[0021] In a second aspect, a smart energy comprehensive regulation device provided by the present application adopts the following technical solutions: A smart energy comprehensive regulation device includes: An acquisition and establishment module, configured to acquire production data and establish a digital twin model based on the production data; A first acquisition module, configured to acquire total energy consumption data and effective energy consumption data based on the digital twin model; A first calculation module, configured to calculate the current energy utilization efficiency based on the total energy consumption data and the effective energy consumption data; A first judgment module, configured to judge whether the current energy utilization efficiency meets a first preset threshold; if the current energy utilization efficiency does not meet the first preset threshold, it transfers to the second acquisition module; The second acquisition module is configured to acquire an adjustment strategy based on the current energy utilization efficiency.

[0022] In a third aspect, a kind of electronic device provided by the present application adopts the following technical solutions: An electronic device includes a processor, and the processor is coupled with a memory; the processor is configured to execute a computer program stored in the memory so that the electronic device executes the method described in the first aspect.

[0023] In a fourth aspect, a computer-readable storage medium provided by the present application adopts the following technical solutions: A computer-readable storage medium includes a computer program or instruction, which, when running on a computer, causes the computer to execute the method described in the first aspect.

[0024] The technical solution of this application obtains corresponding data by establishing a digital twin model, calculates the energy utilization efficiency according to the corresponding data, and further executes an adjustment strategy, achieving the effect of automatically monitoring energy consumption and performing intelligent processing. Description of the Drawings

[0025] Figure 1 is a flowchart of the intelligent energy comprehensive regulation method according to an embodiment of this application.

[0026] Figure 2 is a block diagram of the intelligent energy comprehensive regulation device according to an embodiment of this application.

[0027] Figure 3 is a block diagram of an electronic device according to an embodiment of this application. Detailed Embodiments

[0028] This specific embodiment is only an interpretation of this application and is not a limitation of this application. Those skilled in the art can make modifications to this embodiment without creative contributions according to needs after reading this specification, but as long as they are within the scope of the claims of this application, they are protected by the patent law.

[0029] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Apparently, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without making creative efforts fall within the scope of protection of this application.

[0030] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, unless otherwise specified.

[0031] An embodiment of the present application discloses a comprehensive intelligent energy regulation method. The comprehensive intelligent energy regulation method can be executed by an electronic device. The electronic device can be a server or a terminal device. The server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a desktop computer, etc., but is not limited thereto.

[0032] An embodiment of the present application discloses a comprehensive intelligent energy regulation method. Refer to Figure 1 , the main processes included in a comprehensive intelligent energy regulation method are described as follows (S100~S500): Step S100, obtain production data and establish a digital twin model based on the production data; Step S200, obtain total energy consumption data and effective energy consumption data based on the digital twin model; Step S300, calculate the current energy utilization efficiency based on the total energy consumption data and the effective energy consumption data; Step S400, determine whether the current energy utilization efficiency meets a first preset threshold; if the current energy utilization efficiency does not meet the first preset threshold, then proceed to step S500; Step S500, obtain an adjustment strategy based on the current energy utilization efficiency.

[0033] The electronic device obtains production data and then establishes a digital twin model based on the production data, which can improve the convenience for users to view production data and quickly and intuitively learn about the production situation. The electronic device obtains total energy consumption data and effective energy consumption data based on the digital twin model, and then calculates the current energy utilization efficiency, that is, divides the effective energy consumption data by the total energy consumption data to obtain the current energy utilization efficiency. Then the electronic device determines whether the current energy utilization efficiency meets the first preset threshold, that is, compares the current energy utilization efficiency with the first preset threshold. If the current energy utilization efficiency does not meet the first preset threshold, it indicates that the effective utilization of energy is low at this time. Therefore, the electronic device obtains an adjustment strategy based on the current energy utilization efficiency. Thus, production adjustment is realized to avoid waste of energy.

[0034] Specifically, the adjustment strategy includes: determining whether there is an abnormal energy consumption location based on the digital twin model; if there is an abnormal energy consumption location, obtaining the corresponding current product data based on the abnormal energy consumption location; obtaining the corresponding historical product data based on the abnormal energy consumption location; determining whether the current product data is abnormal based on the historical product data; if the current product data is normal, obtaining the corresponding first production equipment based on the abnormal energy consumption location; outputting a maintenance signal and a production reduction signal based on the first production equipment; if the current product data is abnormal, outputting a stop work signal based on the first production equipment.

[0035] As an alternative implementation manner of the embodiment of the present application, the electronic device determines whether there is an abnormal energy consumption location based on the digital twin model. If there is an energy consumption location, the electronic device obtains the corresponding current product data based on the abnormal energy consumption location, and the electronic device obtains the corresponding historical product data based on the abnormal energy consumption location. Then, it determines whether the current product data is abnormal based on the historical product data. If the current product data is normal, it indicates that the production of the product has not been affected. It can be understood that the effective energy has not changed, but the ineffective energy consumption has increased. Therefore, the electronic device obtains the corresponding first production equipment based on the abnormal energy consumption location, and then the electronic device outputs a maintenance signal and a production reduction signal based on the first production equipment. Because the ineffective energy consumption has increased, it is determined that the first production equipment used for producing the product has an abnormal situation. Therefore, a maintenance signal is output to enable relevant staff to check and maintain. At the same time, in order to reduce the possibility of the situation of the first production equipment deteriorating rapidly, a production reduction signal is also output to reduce the working and running time of the first production equipment. If the current product data is abnormal, it is determined that the situation is relatively serious at this time, so the effective energy consumption is affected. Therefore, at this time, the electronic device outputs a stop work signal to make the first production equipment stop working.

[0036] As an alternative implementation manner of the embodiment of the present application, before outputting the stop work signal based on the first production equipment, it further includes: obtaining the received operation instruction based on the first production equipment; obtaining the production state of the first production equipment before receiving the operation instruction; determining whether the operation instruction meets the operation requirements based on the production state; if the operation instruction does not meet the operation requirements, obtaining a first preset delay; within the first preset delay, determining whether the first production equipment receives a debugging instruction; if the first production equipment receives a debugging instruction, the step of outputting the stop work signal based on the first production equipment is not executed. If the operation instruction meets the preset requirements, the step of outputting the stop work signal based on the first production equipment is executed.

[0037] Before the electronic device outputs a stop working signal based on the first production device, the electronic device obtains the received operation instruction based on the first production device, then obtains the production state before receiving the operation instruction based on the first production device, and then determines whether the operation instruction meets the operation requirements based on the production state. If the operation instruction does not meet the operation requirements, it indicates that a misoperation has occurred at this time. Therefore, at this time, the electronic device obtains a first preset delay, and then determines whether the first production device receives a debugging instruction within the first preset delay. If the first production device receives a debugging instruction, it indicates that the first electronic device has been adjusted from the misoperation situation and has returned to the normal production process. Therefore, the electronic device does not execute the step of outputting a stop working signal based on the first production device, that is, the misoperation is temporary, so there is no need to stop working after the adjustment. If the operation instruction meets the preset requirements, the step of outputting a stop working signal is executed because there is a problem with product production, but it is not caused by a misoperation of the production device. Then it means that a relatively large problem has occurred at this time, so production needs to be stopped.

[0038] As an optional implementation manner of the embodiment of the present application, obtain all historical energy utilization rates; perform trend prediction based on the historical energy utilization rates to obtain a prediction result; correct the first preset threshold based on the prediction result to obtain a correction value; assign the correction value to the first preset threshold.

[0039] The electronic device obtains all historical energy utilization rates, and then the electronic device performs trend prediction based on the historical energy utilization rates to obtain a prediction result. The electronic device corrects the first preset threshold based on the prediction result to obtain a correction value, and then assigns the correction value to the first preset threshold. Because during the production process, with equipment aging and production changes, etc., the energy utilization rate at different time points will change. Therefore, in order to better judge whether the current energy utilization rate is reasonable, it is necessary to adjust the first preset threshold so that the determination can be more accurate.

[0040] Specifically, performing trend prediction based on the historical energy utilization rate to obtain a prediction result includes: The calculation formula for the prediction result is: (Formula 1); Where k is the time point, that is, each historical energy utilization rate corresponds to a time point; is the prediction result at the k + 1th time point; is the original data sequence of the first value, that is is the value of the first historical energy utilization rate; a and b are known numbers.

[0041] Using formula 1, the subsequent predicted value at the current time point can be calculated. By using the calculated predicted value to correct the first preset threshold, the determination result can be made more accurate. Moreover, the predicted value calculated by formula 1 is more accurate and conforms to the production situation. Because there are many uncertain situations in the production process, that is, there are many cases of original data, which easily leads to low reliability of the original data. However, in this case, the result calculated by using formula 1 can be more in line with the actual changes, that is, the obtained predicted value is more accurate. Furthermore, the calculation method of formula 1 has a certain adaptability even when the original data is non-linear data, missing data, etc.

[0042] Construct the original data sequence with historical energy utilization rates ; For the original data sequence Perform accumulation to obtain a new sequence ; Based on the sequence Construct the adjacent mean generation sequence , sequence ; Construct the data matrix B and the vector Y; Based on the calculation formula: Calculate to obtain the parameter vector U; The calculation formula of the parameter vector U is: ; Based on the parameter vector U, the known numbers a and b can be extracted; Among them, Represents the kth historical energy utilization rate; Represents the cumulative value of the historical energy utilization rates from the first to the kth; The data matrix B is a matrix, n is the length of the original data sequence, that is, n is the number of historical energy utilization rates. The first column of the data matrix B is all , and the second column of the data matrix B is all 1; The vector Y is a -dimensional vector. The vector Y includes the values of the second element to the last element of the original data sequence ; Is the transpose matrix of B, Is 's inverse matrix. And, because Is based on And 's mean, so the length of the sequence Will be 1 less than the length of the sequence , that is, for the calculation of the sequence , .

[0043] For example, if the original data sequence , the cumulative generation sequence The calculation is as follows: , , , and so on until calculating to .

[0044] The calculation of the sequence generated adjacent to the mean is as follows: , , and so on until calculating to .

[0045] For constructing the data matrix B, the data matrix B is: .

[0046] For constructing the vector Y, the vector Y is: .

[0047] After that, one can use to calculate the parameter vector U. After solving for U, a and b can be obtained.

[0048] As an alternative implementation of the embodiment of the present application, before correcting the first preset threshold based on the prediction result to obtain a corrected value, it further includes: obtaining an activity log; determining whether the activity log includes improvement data; if the activity log includes improvement data, obtaining a corresponding second evaluation value based on the improvement data; obtaining a first evaluation value before improvement based on the activity log; calculating a change rate based on the first evaluation value and the second evaluation value; determining whether the change rate is greater than a second preset threshold; if the change rate is greater than the second preset threshold, not performing the step of correcting the first preset threshold based on the prediction result to obtain a corrected value; if the change rate is not greater than the second preset threshold, performing the step of correcting the first preset threshold based on the prediction result to obtain a corrected value.

[0049] Before the electronic device corrects the first preset threshold based on the prediction result to obtain a corrected value, the electronic device obtains an activity log, which records various change records during the production process. The electronic device determines whether the activity log includes improvement data. If the activity log includes improvement data, the electronic device obtains a corresponding second evaluation value based on the improvement data. Then the electronic device also obtains a first evaluation value before improvement. After that, the change rate is calculated, that is, the difference is obtained by subtracting the first value from the second evaluation value, and then the change rate is obtained by dividing the difference by the first evaluation value. The electronic device determines whether the change rate is greater than the second preset threshold. If the change rate is greater than the second preset threshold, it indicates that there are significant improvements in the current production, and the improvements include but are not limited to the update of production equipment and the improvement of production processes. In the case of significant improvements, the electronic device does not perform the step of correcting the first preset threshold based on the prediction result to tighten the management of the improved situation rather than loosen the management. At this time, it is also an evaluation of the improvement effect.

[0050] Figure 2 This is a structural block diagram of an intelligent energy comprehensive regulation device 600 provided by an embodiment of the present application. As Figure 2 shown, the intelligent energy comprehensive regulation device 600 includes: An acquisition and establishment module 601, configured to acquire production data and establish a digital twin model based on the production data; A first acquisition module 602, configured to acquire total energy consumption data and effective energy consumption data based on the digital twin model; A first calculation module 603, configured to calculate the current energy utilization efficiency based on the total energy consumption data and the effective energy consumption data; A first judgment module 604, configured to judge whether the current energy utilization efficiency meets a first preset threshold; if the current energy utilization efficiency does not meet the first preset threshold, then transfer to a second acquisition module 605; A second acquisition module 605, configured to acquire an adjustment strategy based on the current energy utilization efficiency.

[0051] Specifically, the second acquisition module 605 includes: A first judgment sub-module, configured to judge whether there is an abnormal energy consumption position based on the digital twin model; if there is an abnormal energy consumption position, then acquire corresponding current product data based on the abnormal energy consumption position; A first acquisition sub-module, configured to acquire corresponding historical product data based on the abnormal energy consumption position; A second judgment sub-module, configured to judge whether the current product data is abnormal based on the historical product data; if the current product data is not abnormal, then acquire a corresponding first production device based on the abnormal energy consumption position; if the current product data is abnormal, then output a stop working signal based on the first production device; A first output sub-module, configured to output a maintenance signal and a production reduction signal based on the first production device.

[0052] In this alternative embodiment, the intelligent energy comprehensive regulation device 600 further includes: A second acquisition sub-module, configured to acquire an operation instruction received by the first production device before outputting a stop working signal based on the first production device; A third acquisition sub-module, configured to acquire the production state before the first production device receives the operation instruction; A third judgment sub-module, configured to judge whether the operation instruction meets the operation requirements based on the production state; if the operation instruction does not meet the operation requirements, then acquire a first preset delay; The fourth judgment sub-module is used to judge whether the first production device receives a debugging instruction within the first preset delay; if the first production device receives a debugging instruction, the step of outputting a stop working signal based on the first production device is not executed. If the operation instruction meets the preset requirements, the step of outputting a stop working signal based on the first production device is executed.

[0053] In this optional embodiment, the intelligent energy comprehensive regulation device 600 further includes: The fourth acquisition sub-module is used to acquire all historical energy utilization rates; The first prediction sub-module is used to perform trend prediction based on historical energy utilization to obtain a prediction result; The first correction sub-module is used to correct the first preset threshold based on the prediction result to obtain a correction value; The first assignment sub-module is used to assign the correction value to the first preset threshold.

[0054] Specifically, the first prediction sub-module includes: The first calculation sub-module is used to calculate the prediction result, and the calculation formula of the prediction result is: ; where k is the time point, that is, each historical energy utilization rate corresponds to a time point; is the prediction result at the k + 1th time point; is the original data sequence the first value of, that is is the value of the first historical energy utilization rate; a and b are known numbers.

[0055] In this optional embodiment, the intelligent energy comprehensive regulation device 600 further includes: The first construction sub-module is used to construct the original data sequence from the historical energy utilization rate ; The first accumulation sub-module is used to accumulate the original data sequence to obtain a new sequence ; The first generation sub-module is used to construct the adjacent mean generation sequence based on the sequence ; the sequence ; ; The second construction sub-module is used to construct the data matrix B and the vector Y; The second calculation sub-module is used to calculate the parameter vector U, and the calculation formula is: ; after deformation, it is obtained ; The first extraction sub-module is used to extract the known numbers a and b based on the parameter vector U; where represents the kth historical energy utilization rate; represents the cumulative value of the historical energy utilization rates from the first to the k-th; the data matrix B is a matrix, where n is the length of the original data sequence, that is, n is the number of historical energy utilization rates. The first column of the data matrix B is all , and the second column of the data matrix B is all 1; the vector Y is a vector of dimension, and the vector Y includes the values of the second element to the last element of the original data sequence ; is the transpose matrix of B, is the inverse matrix of.

[0056] In this alternative embodiment, the intelligent energy comprehensive regulation device 600 further includes: A fifth acquisition sub-module, configured to acquire an activity log before modifying the first preset threshold based on the prediction result to obtain a correction value; A fifth judgment sub-module, configured to judge whether the activity log includes improvement data; if the activity log includes improvement data, then obtain a corresponding second evaluation value based on the improvement data; A sixth acquisition sub-module, configured to acquire a first evaluation value before improvement based on the activity log; A third calculation sub-module, configured to calculate a change rate based on the first evaluation value and the second evaluation value; A sixth judgment sub-module, configured to judge whether the change rate is greater than a second preset threshold; if the change rate is greater than the second preset threshold, then do not perform the step of modifying the first preset threshold based on the prediction result to obtain a correction value; if the change rate is not greater than the second preset threshold, then perform the step of modifying the first preset threshold based on the prediction result to obtain a correction value.

[0057] Figure 3 is a structural block diagram of an electronic device 700 provided by an embodiment of the present application. The electronic device 700 can be a device such as a mobile phone, a tablet computer, a PC, or a server. As Figure 3 shown, the electronic device 700 includes a memory 701, a processor 702, and a communication bus 703; the memory and the processor 702 are connected through the communication bus 703. A computer program capable of being loaded and executed by the processor 702, such as the intelligent energy comprehensive regulation method provided by the above embodiment, is stored on the memory 701.

[0058] The memory 701 can be used to store instructions, programs, codes, code sets, or instruction sets. The memory 701 can include a program storage area and a managed data storage area. Among them, the program storage area can store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the intelligent energy comprehensive regulation method provided by the above embodiment, etc.; the managed data storage area can store managed data involved in the intelligent energy comprehensive regulation method provided by the above embodiment, etc.

[0059] The processor 702 may include one or more processing cores. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 701, the processor 702 invokes the managed data stored in the memory 701 and performs various functions of this application and processes the managed data. The processor 702 may be at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor. It can be understood that for different devices, the electronic devices for implementing the functions of the above-mentioned processor 702 may also be others, and the embodiments of this application do not make specific limitations.

[0060] The communication bus 703 may include a path for transmitting information between the above components. The communication bus 703 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 703 may be divided into an address bus, a managed data bus, a control bus, etc. For the sake of representation, Figure 3 only a double arrow is used herein, but it does not mean that there is only one bus or one type of bus.

[0061] The embodiments of this application provide a computer storage medium storing a computer program that can be loaded and executed by a processor to perform the intelligent energy comprehensive regulation method provided in the above embodiments.

[0062] In this embodiment, a computer storage medium may be a tangible device that holds and stores instructions used by an instruction execution device. The computer storage medium may be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination of the foregoing. Specifically, the computer storage medium may be a portable computer disk, a hard disk, a USB flash drive, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, an optical disc, a magnetic disc, a mechanical encoding device, and any combination of the foregoing.

[0063] The term "comprising," "including," or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or apparatus.

Claims

1. A comprehensive regulation method for intelligent energy, characterized in that, Including: Obtain production data and establish a digital twin model based on the production data; Obtain total energy consumption data and effective energy consumption data based on the digital twin model; Calculate the current energy utilization efficiency based on the total energy consumption data and the effective energy consumption data; Determine whether the current energy utilization efficiency meets a first preset threshold; If the current energy utilization efficiency does not meet the first preset threshold, obtain an adjustment strategy based on the current energy utilization efficiency.

2. The intelligent energy comprehensive regulation method according to claim 1, characterized in that The adjustment strategy includes: Based on the digital twin model, determine whether there is an abnormal energy consumption position; If there is an abnormal energy consumption position, obtain corresponding current product data based on the abnormal energy consumption position; Obtain corresponding historical product data based on the abnormal energy consumption position; Based on the historical product data, determine whether the current product data is abnormal; If the current product data is not abnormal, obtain a corresponding first production device based on the abnormal energy consumption position; Output a maintenance signal and a production reduction signal based on the first production device; If the current product data is abnormal, output a stop working signal based on the first production device.

3. The integrated control method of smart energy according to claim 2, characterized in that Before outputting the stop working signal based on the first production device, it further includes: Obtain the received operation instruction based on the first production device; Obtain the production state before receiving the operation instruction based on the first production device; Based on the production state, determine whether the operation instruction meets the operation requirements; If the operation instruction does not meet the operation requirements, obtain a first preset delay; Within the first preset delay, determine whether the first production device receives a debugging instruction; If the first production device receives the debugging instruction, do not execute the step of outputting the stop working signal based on the first production device; If the operation instruction meets the preset requirements, execute the step of outputting the stop working signal based on the first production device.

4. The intelligent energy comprehensive regulation method according to claim 1, characterized in that The method further includes: Obtain all historical energy utilization rates; Perform trend prediction based on the historical energy utilization to obtain a prediction result; Correct the first preset threshold based on the prediction result to obtain a correction value; Assign the correction value to the first preset threshold.

5. The integrated control method for intelligent energy according to claim 4, wherein, The performing trend prediction based on the historical energy utilization rate to obtain a prediction result includes: The calculation formula for the predicted result is as follows: ; Among them, k is the time point, that is, each historical energy utilization rate corresponds to a time point; is the prediction result at the (k + 1)-th time point; is the original data sequence the first value of, that is is the value of the first historical energy utilization rate; a and b are known numbers.

6. A comprehensive intelligent energy regulation method according to claim 5, characterized in that The method further includes: Construct the original data sequence of historical energy utilization rate ; Accumulate the original data sequence to obtain a new sequence ; Sequence-based Construct a sequence generated adjacent to the mean , sequence ; Construct a data matrix B and a vector Y; Based on the calculation formula: , the parameter vector U is calculated; The calculation formula for the parameter vector U is as follows: ; Based on the parameter vector U, the known numbers a and b can be extracted; Among them, represents the k-th historical energy utilization rate; represents the cumulative value of the historical energy utilization rates from the first to the k-th; the data matrix B is matrix, where n is the length of the original data sequence, that is, n is the number of historical energy utilization rates. The first column of the data matrix B is all , and the second column of the data matrix B is all 1; the vector Y is dimensional vector, and the vector Y includes the original data sequence from the second element to the last element; is the transpose matrix of B, is inverse matrix.

7. A comprehensive intelligent energy regulation method according to claim 5, characterized in that Before correcting the first preset threshold based on the prediction result to obtain a correction value, it further includes: Obtain an activity log; Determine whether the activity log includes improvement data; If the activity log includes improvement data, obtain a corresponding second evaluation value based on the improvement data; Obtain a first evaluation value before improvement based on the activity log; Calculate a change rate based on the first evaluation value and the second evaluation value; Determine whether the change rate is greater than a second preset threshold; If the change rate is greater than the second preset threshold, do not execute the step of correcting the first preset threshold based on the prediction result to obtain a correction value; If the change rate is not greater than the second preset threshold, perform the step of correcting the first preset threshold based on the prediction result to obtain a corrected value.

8. An integrated intelligent energy regulation device, characterized in that, Comprising: An acquisition and establishment module, configured to acquire production data and establish a digital twin model based on the production data; A first acquisition module, configured to acquire total energy consumption data and effective energy consumption data based on the digital twin model; A first calculation module, configured to calculate the current energy utilization efficiency based on the total energy consumption data and the effective energy consumption data; A first judgment module, configured to judge whether the current energy utilization efficiency meets a first preset threshold; If the current energy utilization efficiency does not meet the first preset threshold, transfer to the second acquisition module; The second acquisition module is configured to acquire an adjustment strategy based on the current energy utilization efficiency.

9. An electronic device, characterized in that, Comprising a processor, the processor is coupled to a memory; the processor is configured to execute a computer program stored in the memory, so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Comprising a computer program or instruction, when the computer program or instruction runs on a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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