Energy management system based on industrial Internet of Things

Abstract

The invention discloses an energy management system based on industrial Internet of Things, which comprises a data collection module, an equipment management module and an energy management module, and is characterized in that the data collection module is used for collecting equipment power consumption data of an enterprise, comprehensive information of a product and comprehensive data of equipment; the equipment management module is used for monitoring voltage, current and electricity consumption data of the equipment in the operation process, and the energy management module is used for predicting the energy consumption of the equipment, judging whether the actual energy consumption of the equipment meets the expectation or not, and adjusting the operation mode of the equipment according to the judgment result. The data collection module, the equipment management module and the energy management module are electrically connected with one another, the data collection module comprises a power utilization data collection module, a product comprehensive information input module and an equipment comprehensive data input module, and the power utilization data collection module is used for collecting voltage of equipment in the operation process. The method has the characteristics of improving energy utilization rate and production efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy management, and particularly to an energy management system based on industrial Internet of Things. Background Art

[0002] With the continuous development of China's industry and social progress, at present, most industrial enterprises are developing towards energy conservation and emission reduction. Many enterprises have begun to monitor the energy consumption of industrial production equipment, adjust the power of the equipment to control energy consumption, and achieve the purpose of increasing production benefits. However, due to the numerous factors affecting the energy consumption of industrial production equipment, the existing technology cannot accurately analyze the relationship between the production rate of the equipment and the production energy consumption, resulting in high energy consumption of enterprises and low production efficiency. Moreover, due to the different power consumption of each production line in the industrial park, the existing technology cannot evenly distribute the electric energy required by each production line during the peak electricity consumption period, resulting in some equipment not being able to obtain sufficient energy supply, leading to a decrease in the production rate of the equipment or even a risk of downtime. Therefore, it is necessary to design an energy management system based on industrial Internet of Things to improve energy utilization efficiency and production efficiency. Summary of the Invention

[0003] The purpose of the present invention is to provide an energy management system based on industrial Internet of Things to solve the problems raised in the above background art.

[0004] To solve the above technical problems, the present invention provides the following technical solutions: An energy management system based on industrial Internet of Things, including a data collection module, an equipment management module, and an energy management module, characterized in that: the data collection module is used to collect the equipment power consumption data, comprehensive information of products, and comprehensive data of equipment of an enterprise; the equipment management module is used to monitor the voltage, current, and power consumption data of the equipment during operation and calculate the operating power of the equipment; the energy management module is used to predict the energy consumption of the equipment, judge whether the actual energy consumption of the equipment meets the expectation, and adjust the operating mode of the equipment according to the judgment result; the data collection module, the equipment management module, and the energy management module are electrically connected to each other;

[0005] The energy efficiency analysis module includes an energy consumption analysis sub-module, an energy efficiency calculation sub-module, and a load calculation sub-module. The energy consumption analysis sub-module is used to analyze whether the energy consumption of the equipment is normal and analyze the reasons for abnormal energy consumption. The energy efficiency calculation sub-module is used to analyze the relationship between the energy consumption of the equipment and the production rate, and calculate the optimal production rate of the equipment according to the analysis result. The load analysis sub-module is used to analyze the load status of the equipment and the power transmission line during the operation of the equipment;

[0006] The device monitoring module includes a power calculation module and an electrical parameter detection sub-module. The power calculation module is used to calculate the power of the device and the power at the power supply end during the operation of the device. The electrical parameter detection sub-module is used to detect the electrical parameters in the power system during the operation of the device.

[0007] According to the above technical solution, the data collection module includes an electricity consumption data collection module, a product comprehensive information input module, and a device comprehensive data input module. The electricity consumption data collection module is used to collect the voltage, current, and electrical parameters transmitted by the power supply end during the operation of the device. The product comprehensive information input module is used to input the comprehensive data of the product to be produced into the system. The device comprehensive data input module is used to input the historical production record information of the device into the system.

[0008] According to the above technical solution, the device management module includes an energy efficiency analysis module and a device monitoring module. The energy efficiency analysis module is used to analyze the energy consumption of the device, analyze whether the product to be produced has sufficient processing benefits, and calculate the production rate of the device when the enterprise has the highest revenue according to the analysis results. The device monitoring module is used to monitor the electrical parameters and power of the device and the power supply end during the operation of the device.

[0009] According to the above technical solution, the energy management module includes an energy consumption prediction module. The energy consumption prediction module is used to predict the energy consumption of the device for processing a batch of products according to the current energy consumption situation of the device.

[0010] According to the above technical solution, the energy management module further includes a power adjustment module. The power adjustment module is used to adjust the power transmitted by the power supply end according to the energy consumption analysis situation of the device and the electrical parameters during the operation of the device.

[0011] According to the above technical solution, the operation method of the energy management system mainly includes the following steps:

[0012] Step S1: Through the electricity consumption data collection module, collect the comprehensive electricity consumption data of the device in real time during operation. Through the product comprehensive information input module, input the comprehensive information data of the product to be produced into the system. Through the device neutral data input module, input the historical production data of the device into the system;

[0013] Step S2: When the device processes the product, the system triggers the start of the energy efficiency analysis module, and starts to analyze the relationship between the energy consumption and production rate of the device for processing this product, and adjusts the processing mode of the device according to the analysis results;

[0014] Step S3: During the production process of the product, the system starts the device monitoring module, and starts to analyze the load situation, power, and circuit parameters of the device and the power supply line during the operation of the device, and adjusts the energy supply of the device according to the analysis results;

[0015] Step S4: When adjusting the energy supply, predict the energy consumption required for the equipment to process products according to the equipment processing mode, compare and analyze the actual energy consumption, and adjust the power supply at the power supply end according to the analysis results.

[0016] According to the above technical solution, the step S2 further includes the following steps:

[0017] Step S21: Retrieve the data of the product to be processed, identify the number of the product to be processed and the corresponding processing quantity M, retrieve the production energy consumption Q corresponding to the processing quantity from the historical database according to the number and the processing quantity, that is, the total electric energy consumed to produce M products, and give the influence coefficient α of the data volume of the processed product on the production energy consumption;

[0018] Step S22: Obtain the comprehensive product information data, identify the model, brand and name of the product, retrieve the historical sales price of the product according to the model, brand and name of the product, and give the error coefficient β of the product selling price according to the change trend of the historical sales price;

[0019] Step S23: Calculate the theoretical profit of producing this batch of products according to the formula In the formula, i = 1, 2, 3......n, P1 represents the theoretical profit of producing this batch of products, β represents the error coefficient of the product selling price, P2 represents the selling price of the processed product, P3 represents the unit price of electric energy consumption. If the theoretical profit of producing this batch of products is greater than the system set threshold, the product is marked as a processable product, otherwise the product is marked as an unprocessable product.

[0020] According to the above technical solution, the step S23 further includes the following steps:

[0021] Step S231: Retrieve the comprehensive equipment data, identify the historical production rate of the equipment and the corresponding production energy consumption, that is, the electric energy consumed per unit time at the current production rate, give the influence coefficient κ of the equipment production rate on the electric energy consumption, and calculate the predicted profit P of producing this batch of products through the formula 预 = ν·T(β·P2 - α·κ·J·P3), in the formula, P 预 represents the predicted profit of producing this batch of products, ν represents the current production rate of the equipment, T represents the time required to produce the current product, κ represents the influence coefficient of the current production rate of the equipment on the electric energy required for the equipment to produce one product, J represents the rated electric energy required for the equipment to process one product. Sort the predicted profits in descending order, mark the production rate corresponding to the predicted profit in the first place, and the system sets this production rate as the current production rate of the equipment;

[0022] Step S232: Retrieve the historical database according to the production rate of the device, give the device power corresponding to the current device production rate, and calculate the line load of the current transmission line through the formula In the formula, F represents the load of the current transmission line, W represents the rated power of the device at the current production rate, η represents the power factor, L represents the length of the transmission line between devices, S represents the cross-sectional area of the transmission line. When the line load value of the transmission line is greater than the system-set threshold, anchor the devices connected by this line, identify the line code, retrieve the database according to the line code, give the maximum line load allowed for the current line, and calculate the operating power W of the device under this line load through the above formula m , compare with the database and calculate W m The power difference between W and the power of the device at each production rate in the database. If there exists W m The power difference between W and the power of the device at each production rate in the database is less than the threshold, then mark this production rate, sort the production rates in descending order, and select the first production rate as the production rate of the device. Otherwise, the system continues to detect

[0023] According to the above technical solution, step S3 further includes the following steps

[0024] Step S31: Obtain the output parameters of the power supply, identify the output voltage U1 and current I1 of the power supply, retrieve the corresponding power loss coefficient μ of the electric energy in the data according to the output current of the power supply, and calculate the electric power output by the power supply to reach the power W of the device through the formula 电 =U1·I1·μ. In the formula, W 电 Represents the electric power output by the power supply to reach the power of the device. Retrieve the comprehensive data of the device, identify the actual voltage and actual current of the device, and calculate the electric power required by the device through the formula 需 =U2·I2. In the formula, W 需 Represents the electric power required by the device, U2 represents the actual voltage of the device, I2 represents the actual current of the device. When W 电 >W 需 , then calculate the difference W 电 Between W and W 需 The difference value W 调 =W 电 -W 需 . In the formula, W 调 Represents the difference between W 电 And W 需 . If the difference between W 电 And W 需 Is greater than the threshold, then mark the current power supply as a dispatchable power supply. Otherwise, the system continues to detect. When W 电 <W 需 , then mark the current power supply as a demand power supply

[0025] Step S32: Identify the marks in the power supply. When the power supply is a demand power supply, retrieve the required electric power of the demand power supply, retrieve the adjacent dispatchable power supplies, identify the dispatchable electric power values. If the electric power value is greater than the required electric power of the demand power supply, retrieve the surplus electric power of the dispatchable power supply to compensate the demand power supply; otherwise, retrieve the surplus electric power of other adjacent dispatchable power supplies for compensation.

[0026] According to the above technical solution, in step S4, retrieve the comprehensive data of the equipment, identify the rated power P of the equipment, and calculate the predicted electric energy required to produce this batch of products through the formula. In the formula, Q 预 represents the predicted electric energy required to produce this batch of products, λ represents the influence coefficient of the equipment power fluctuation on the required electric energy. Set the detection period, retrieve the electric energy actually consumed by the equipment within the period, calculate the difference between the actually consumed electric energy of the equipment and the predicted electric energy. When the electric energy difference is less than the threshold, mark the equipment as a normal equipment; when the electric energy difference is greater than the threshold, retrieve the actual voltage and current of the equipment. If the difference between the actual voltage and current of the equipment and the current and voltage in the database is less than the threshold, mark that the equipment has a fault; otherwise, mark it as a transmission line fault and notify the management staff for maintenance.

[0027] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In the present invention, by calculating the theoretical profit of the product before processing the product, it is possible to determine whether the profit of the product meets the requirements, avoiding misjudgment by enterprises when determining whether a product has production value, and preventing enterprises from wasting resources in producing low-value products, resulting in low enterprise profits. Furthermore, it greatly improves the energy utilization rate of enterprises. By analyzing the relationship between the production rate of the equipment and the pre-production energy consumption, it is possible to ensure that the equipment processes products at the optimal production rate with limited energy, enabling the equipment to reach the best balance state between efficiency and energy consumption, greatly reducing the equipment energy consumption, and improving the energy utilization rate. By predicting the load of the transmission line, it is possible to avoid the line being overloaded due to excessive power, resulting in short circuits and danger, greatly improving the safety of workshop workers. By judging whether the electric power provided by the power supply can meet the normal operation of the equipment, it is possible to use the surplus electric power to compensate the demand power supply, thereby enabling the equipment to operate at the best production rate, greatly improving the production efficiency of the equipment. By compensating the surplus electric power of the adjacent power supply to the demand power supply, it is possible to ensure that the power supply with insufficient electric power can provide sufficient electric power for the equipment, ensuring the normal operation of the equipment, greatly improving the production efficiency of the equipment, and at the same time, it is also possible to avoid the waste of the surplus electric power of the power supply with surplus electric power after meeting the normal operation of the equipment, reducing energy waste, and greatly improving the energy utilization rate. By comparing the predicted consumed electric energy with the actual consumed electric energy, it is possible to quickly determine whether the operation state of the equipment is normal, ensure that the equipment can be repaired in time, reduce the equipment downtime, and greatly improve the production efficiency of the equipment. Brief Description of the Drawings

[0028] The accompanying drawings are used to provide a further understanding of the present invention and form a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0029] Figure 1 It is a schematic diagram of the system module composition of the present invention. Detailed Embodiments

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0031] Please refer to Figure 1 , the present invention provides a technical solution: an energy management system based on industrial Internet of Things, including a data collection module, a device management module, and an energy management module, characterized in that: the data collection module is used to collect the equipment power consumption data of an enterprise, the comprehensive information of products, and the comprehensive data of equipment; the device management module is used to monitor the voltage, current, and power consumption data of the equipment during operation and calculate the operating power of the equipment; the energy management module is used to predict the energy consumption of the equipment, judge whether the actual energy consumption of the equipment meets the expectation, and adjust the operating mode of the equipment according to the judgment result; the data collection module, the device management module, and the energy management module are electrically connected to each other;

[0032] The energy efficiency analysis module includes an energy consumption analysis sub-module, an energy efficiency calculation sub-module, and a load calculation sub-module. The energy consumption analysis sub-module is used to analyze whether the energy consumption of the equipment is normal and analyze the reasons for abnormal energy consumption. The energy efficiency calculation sub-module is used to analyze the relationship between the energy consumption of the equipment and the production rate, and calculate the optimal production rate of the equipment according to the analysis result. The load analysis sub-module is used to analyze the load conditions of the equipment and the power transmission line during the operation of the equipment;

[0033] The device monitoring module includes a power calculation module and an electrical parameter detection sub-module. The power calculation module is used to calculate the power of the equipment and the power at the power supply end during the operation of the equipment. The electrical parameter detection sub-module is used to detect the electrical parameters in the power system during the operation of the equipment.

[0034] The data collection module includes an electricity consumption data collection module, a product comprehensive information input module, and an equipment comprehensive data input module. The electricity consumption data collection module is used to collect the voltage, current, and power parameters transmitted by the power supply end during the operation of the equipment. The product comprehensive information input module is used to input the comprehensive data of the product to be produced into the system. The equipment comprehensive data input module is used to input the historical production record information of the equipment into the system.

[0035] The equipment management module includes an energy efficiency analysis module and an equipment monitoring module. The energy efficiency analysis module is used to analyze the energy consumption of the equipment, analyze whether the product to be produced has sufficient processing benefits, and calculate the production rate of the equipment when the enterprise has the highest revenue according to the analysis results. The equipment monitoring module is used to monitor the power parameters of the equipment and the power supply end during the operation of the equipment and the power of the equipment.

[0036] The energy management module includes an energy consumption prediction module, which is used to predict the energy consumption of the equipment for processing a batch of products according to the current energy consumption situation of the equipment.

[0037] The energy management module also includes an electric energy adjustment module, which is used to adjust the electric energy transmitted by the power supply end according to the energy consumption analysis of the equipment and the power parameters during the operation of the equipment.

[0038] The operation method of the energy management system mainly includes the following steps:

[0039] Step S1: Through the electricity consumption data collection module, the comprehensive electricity consumption data of the equipment during operation is collected in real time. Through the product comprehensive information input module, the comprehensive information data of the product to be produced is input into the system. Through the equipment neutral data input module, the historical production data of the equipment is input into the system;

[0040] Step S2: When the equipment processes the product, the system triggers the start of the energy efficiency analysis module to start analyzing the relationship between the energy consumption and production rate of the equipment for processing this product, and adjusts the processing mode of the equipment according to the analysis results;

[0041] Step S3: During the product production process, the system starts the equipment monitoring module to start analyzing the load situation, power, and circuit parameters of the equipment and the power supply line during the operation of the equipment, and adjusts the energy supply of the equipment according to the analysis results;

[0042] Step S4: When adjusting the energy supply, predict the energy consumption required for the equipment to process the product according to the equipment processing mode, compare and analyze the actual energy consumption, and adjust the electric energy supply of the power supply end according to the analysis results.

[0043] Step S2 further includes the following steps:

[0044] Step S21: Retrieve the data of the product to be processed, identify the product number and the corresponding processing quantity M, retrieve the production energy consumption Q corresponding to the processing quantity from the historical database according to the number and processing quantity, that is, the total electric energy consumed for producing M products, and give the influence coefficient α of the data volume of the product to be processed on the production energy consumption;

[0045] Step S22: Obtain the comprehensive product information data, identify the model, brand and name of the product, retrieve the historical sales price of the product according to the model, brand and name of the product, and give the error coefficient β of the product selling price according to the historical sales price change trend;

[0046] Step S23: Calculate the theoretical profit of producing this batch of products according to the formula In the formula, i = 1, 2, 3......n, P1 represents the theoretical profit of producing this batch of products, β represents the error coefficient of the product selling price, P2 represents the selling price of the product to be processed, P3 represents the unit price of power energy consumption. If the theoretical profit of producing this batch of products is greater than the system-set threshold, the product will be marked as a processable product; otherwise, the product will be marked as an unprocessable product. By calculating the theoretical profit of the product before processing, it is possible to determine whether the profit of the product meets the requirements, avoid misjudgment by the enterprise when determining whether the product has production value, prevent the enterprise from wasting resources in producing low-value products, resulting in low enterprise profits, and thus greatly improve the energy utilization rate of the enterprise.

[0047] Step S23 further includes the following steps:

[0048] Step S231: Retrieve the comprehensive equipment data, identify the historical production rate of the equipment and the corresponding production energy consumption, that is, the electric energy consumed per unit time at the current production rate, and give the influence coefficient κ of the equipment production rate on the electric energy consumption. Calculate the predicted profit P of producing this batch of products through the formula 预 = ν·T(β·P2 - α·κ·J·P3), where P 预 represents the predicted profit of producing this batch of products, ν represents the current production rate of the equipment, T represents the time required to produce the current product, κ represents the influence coefficient of the current production rate of the equipment on the electric energy required to produce one product by the equipment, J represents the rated electric energy required for the equipment to process one product. Sort the predicted profits in descending order, mark the production rate corresponding to the predicted profit in the first place, and the system will set this production rate as the current production rate of the equipment. By analyzing the relationship between the equipment production rate and the pre-production energy consumption, it is possible to ensure that the equipment processes products at the optimal production rate with limited energy, enabling the equipment to reach the best balance state between efficiency and energy consumption, greatly reducing the equipment energy consumption, and improving the energy utilization rate;

[0049] Step S232: Retrieve the historical database according to the production rate of the device, give the device power corresponding to the current device production rate, and calculate the line load of the current transmission line through the formula In the formula, F represents the load of the current transmission line, W represents the rated power of the device at the current production rate, η represents the power factor, L represents the length of the transmission line between devices, S represents the cross-sectional area of the transmission line. When the line load value of the transmission line is greater than the system-set threshold, anchor the devices connected to this line, identify the line code, retrieve the database according to the line code, give the maximum allowable line load of the current line, and calculate the operating power W of the device under this line load through the above formula m , compare with the database and calculate W m The power difference between W and the power of the device at each production rate in the database. If there exists W m The power difference between W and the power of the device at each production rate in the database is less than the threshold, then mark this production rate and sort the production rates in descending order, select the first production rate as the production rate of the device. Otherwise, the system continues to detect. By predicting the load of the transmission line, it is possible to avoid the line being overloaded due to excessive power, resulting in short circuits and danger, and greatly improving the safety of workshop workers.

[0050] Step S3 further includes the following steps:

[0051] Step S31: Obtain the output parameters of the power supply, identify the output voltage U1 and current I1 of the power supply, retrieve the power loss coefficient μ corresponding to the electric energy in the data according to the output current of the power supply, and calculate the electric power output from the power supply to reach the power W of the device through the formula 电 = U1·I1·μ. In the formula, W 电 Represents the power of the electric power output from the power supply reaching the device. Retrieve the comprehensive data of the device, identify the actual voltage and actual current of the device, and calculate the electric power required by the device through the formula 需 = U2·I2. In the formula, W 需 Represents the electric power required by the device, U2 represents the actual voltage of the device, and I2 represents the actual current of the device. When W 电 > W 需 , then calculate the difference W 电 Between W and W 需 W 调 = W 电 - W 需 , in the formula, W 调 Represents the difference between W 电 And W 需 . If the difference between W 电 And W 需 Is greater than the threshold, then mark the current power supply as a dispatchable power supply. Otherwise, the system continues to detect. When W 电 < W需 When it is, mark the current power supply as the required power supply. By judging whether the electric power provided by the power supply can meet the normal operation of the equipment, the surplus electric power can be used to compensate the required power supply, so that the equipment can operate at the best production rate, greatly improving the production efficiency of the equipment;

[0052] Step S32: Identify the mark in the power supply. When the power supply is the required power supply, retrieve the required electric power of the required power supply, retrieve the adjacent dispatchable power supply, identify the dispatchable electric power value. If the electric power value is greater than the required electric power of the required power supply, retrieve the surplus electric power of the retrievable power supply to compensate the required power supply. Otherwise, retrieve the surplus electric power of other adjacent retrievable power supplies for compensation. By compensating the surplus electric power of the adjacent power supply to the required power supply, it can ensure that the power supply with insufficient electric power can provide sufficient electric power for the equipment, ensure the normal operation of the equipment, greatly improve the production efficiency of the equipment, and at the same time, it can also avoid the waste of the surplus electric power of the power supply with surplus electric power after meeting the normal operation of the equipment, reduce the waste of energy, and greatly improve the energy utilization rate.

[0053] In step S4, retrieve the comprehensive data of the equipment, identify the rated power P of the equipment, and calculate the predicted electric energy required to produce this batch of products through the formula In the formula, Q 预 represents the predicted electric energy required to produce this batch of products, λ represents the influence coefficient of the equipment power fluctuation on the required electric energy. Set the detection period, retrieve the electric energy actually consumed by the equipment within the period, calculate the difference between the electric energy actually consumed by the equipment and the predicted electric energy. When the electric energy difference is less than the threshold value, mark the equipment as a normal equipment. When the electric energy difference is greater than the threshold value, retrieve the actual voltage and current of the equipment. If the difference between the actual voltage and current of the equipment and the current and voltage in the database is less than the threshold value, mark that the equipment has a fault. Otherwise, mark it as a transmission line fault and notify the management personnel for maintenance. By comparing the predicted consumed electric energy with the actual consumed electric energy, it can quickly judge whether the operation state of the equipment is normal, ensure that the equipment can be repaired in time, reduce the downtime of the equipment, and greatly improve the production efficiency of the equipment.

[0054] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0055] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An energy management system based on industrial Internet of Things, including a data collection module, a device management module and an energy management module, characterized in that: The data collection module is used to collect the equipment power consumption data of the enterprise, the comprehensive information of the products and the comprehensive data of the equipment. The equipment management module is used to monitor the voltage, current and power consumption data of the equipment during operation and calculate the operating power of the equipment. The energy management module is used to predict the energy consumption of the equipment, determine whether the actual energy consumption of the equipment meets the expectations, and adjust the operation mode of the equipment according to the determination result. The data collection module, the equipment management module and the energy management module are electrically connected to each other; The energy efficiency analysis module includes an energy consumption analysis submodule, an energy efficiency calculation submodule and a load calculation submodule. The energy consumption analysis submodule is used to analyze whether the energy consumption of the equipment is normal and analyze the cause of abnormal energy consumption. The energy efficiency calculation submodule is used to analyze the relationship between the energy consumption of the equipment and the production rate, and calculate the optimal production rate of the equipment according to the analysis results. The load analysis submodule is used to analyze the load status of the equipment and the power transmission line during the operation of the equipment; The equipment monitoring module includes a power calculation module and an electric power parameter detection submodule. The power calculation module is used to calculate the power of the equipment and the power of the power supply end during operation. The electric power parameter detection submodule is used to detect the electric power parameters in the electric power system of the equipment during operation.

2. The energy management system based on industrial Internet of Things according to claim 1 is characterized in that: The data collection module includes an electricity consumption data collection module, a product comprehensive information entry module and an equipment comprehensive data entry module. The electricity consumption data collection module is used to collect the voltage, current and power parameters transmitted by the power supply end during the operation of the equipment. The product comprehensive information entry module is used to enter the comprehensive data of the products to be produced into the system. The equipment comprehensive data entry module is used to enter the historical production record information of the equipment into the system.

3. The energy management system based on industrial Internet of Things according to claim 2 is characterized in that: The equipment management module includes an energy efficiency analysis module and an equipment monitoring module. The energy efficiency analysis module is used to analyze the energy consumption of the equipment, analyze whether the products to be produced have sufficient processing income, and calculate the production rate of the equipment when the enterprise income is the highest based on the analysis results. The equipment monitoring module is used to monitor the power parameters of the equipment and the power supply end during the operation of the equipment and the power of the equipment.

4. The energy management system based on industrial Internet of Things according to claim 3 is characterized in that: The energy management module includes an energy consumption prediction module, which is used to predict the energy consumption of the equipment for processing a batch of products according to the current energy consumption of the equipment.

5. The energy management system based on industrial Internet of Things according to claim 4 is characterized in that: The energy management module also includes an electric energy adjustment module, which is used to adjust the electric power transmitted by the power supply end according to the energy consumption analysis of the equipment and the electric power parameters during the operation of the equipment.

6. The energy management system based on industrial Internet of Things according to claim 5 is characterized in that: The operation method of the energy management system mainly includes the following steps: Step S1: Collect the comprehensive power consumption data of the equipment in real time during operation through the power consumption data collection module, enter the comprehensive information data of the products to be produced into the system through the product comprehensive information entry module, and enter the historical production data of the equipment into the system through the equipment neutralization data entry module; Step S2: When the equipment processes a product, the system triggers the energy efficiency analysis module to start, and starts to analyze the relationship between the energy consumption and production rate of the equipment for processing the product, and adjusts the processing mode of the equipment according to the analysis results; Step S3: During the product production process, the system starts the equipment monitoring module, starts analyzing the load conditions, power and circuit parameters of the equipment and power supply lines during the equipment operation, and adjusts the energy supply of the equipment according to the analysis results; Step S4: When adjusting the energy supply, the energy consumption required for the equipment to process the product is predicted according to the equipment processing mode, the actual energy consumption is compared and analyzed, and the power supply of the power supply end is adjusted according to the analysis result.

7. The energy management system based on industrial Internet of Things according to claim 6 is characterized in that: The step S2 further comprises the following steps: Step S21: retrieve the data of the product to be processed, identify the number of the product to be processed and the corresponding processing quantity M, retrieve the production energy consumption Q corresponding to the processing quantity in the historical database according to the number and the processing quantity, that is, the total electric energy consumed to produce M products, and give the influence coefficient α of the amount of product data to the production energy consumption; Step S22: Obtain comprehensive product information data, identify the model, brand and name of the product, retrieve the historical sales price of the product according to the model, brand and name of the product, and provide an error coefficient β of the product selling price according to the historical sales price change trend; Step S23: Calculate the theoretical profit of producing this batch of products according to the formula In the formula, i=1,2,3......n, P1 represents the theoretical profit of producing this batch of products, β represents the error coefficient of the product selling price, P2 represents the selling price of the processed products, and P3 represents the unit price of electricity consumption. If the theoretical profit of producing this batch of products is greater than the threshold set by the system, the products will be marked as processable products, otherwise they will be marked as non-processable products.

8. The energy management system based on industrial Internet of Things according to claim 7 is characterized in that: The step S23 further comprises the following steps: Step S231: retrieve the equipment comprehensive data, identify the equipment's historical production rate and the corresponding production energy consumption, that is, the electric energy consumed per unit time at the current production rate, give the influence coefficient κ of the equipment's production rate on the electric energy consumption, and calculate the predicted profit P of producing the batch of products through the formula 预 =ν·T(β·P2-α·κ·J·P3), where, P 预 represents the predicted revenue of producing this batch of products, ν represents the production rate of the current equipment, T represents the time required to produce the current product, κ represents the influence coefficient of the production rate of the current equipment on the electric energy required for the equipment to produce one product, and J represents the rated electric energy required for the equipment to process one product. The predicted revenue is sorted in descending order, and the production rate corresponding to the first-ranked predicted revenue is marked. The system sets this production rate as the production rate of the current equipment; Step S232: Search the historical database according to the production rate of the equipment, give the equipment power corresponding to the current equipment production rate, and calculate the line load of the current transmission line through the formula In the formula, F represents the load of the current transmission line, W represents the rated power of the equipment at the current production rate, η represents the power factor, L represents the length of the transmission line between the equipment, and S represents the cross-sectional area of ​​the transmission line. When the line load value of the transmission line is greater than the system set threshold, the line connection device is anchored, the line code is identified, and the database is retrieved according to the line code to give the maximum line load allowed by the current line. The operating power W of the equipment under the line load is calculated by the above formula m , compare the database and calculate W m The power difference between the equipment at each production rate in the database, if there is W m If the power difference between the equipment at each production rate in the database is less than the threshold, the production rate is marked, and the production rates are sorted in descending order. The first production rate is selected as the production rate of the equipment. Otherwise, the system continues to detect.

9. The energy management system based on industrial Internet of Things according to claim 8 is characterized in that: The step S3 further comprises the following steps: Step S31: Obtain the output parameters of the power supply, identify the voltage U1 and current I1 output by the power supply, retrieve the power loss coefficient μ of the corresponding electric energy in the data according to the output current of the power supply, and calculate the power W of the output electric power of the power supply to the device through the formula 电 =U1·I1·μ, where W 电 Indicates the power output of the power supply reaching the device. Retrieve the comprehensive data of the device, identify the actual voltage and current of the device, and calculate the power W required by the device through the formula 需 =U2·I2, where W 需 Indicates the electrical power required by the device, U2 indicates the actual voltage of the device, and I2 indicates the actual current of the device. 电 >W 需 When W 电 With W 需 The difference W 调 =W 电 -W 需 , where W 调 W 电 With W 需 If W 电 With W 需 If the difference between W and W is greater than the threshold, the current power source is marked as a dispatchable power source. Otherwise, the system continues to detect. 电 <W 需 , the current power source is marked as the required power source; Step S32: Identify the mark in the power supply. When the power supply is the demand power supply, call the electric power required by the demand power supply, call the adjacent dispatchable power supply, and identify the dispatchable electric power value. If the electric power value is greater than the electric power required by the demand power supply, call the surplus electric power of the dispatchable power supply to compensate for the demand power supply. Otherwise, call the surplus electric power of other adjacent dispatchable power supplies for compensation.

10. The energy management system based on industrial Internet of Things according to claim 9, characterized in that: In step S4, the comprehensive data of the equipment is retrieved, the rated power P of the equipment is identified, and the predicted electric energy required to produce the batch of this product is calculated by the formula. In the formula, Q 预 It represents the predicted electric energy required to produce this batch of this product, λ represents the influence coefficient of equipment power fluctuation on the required electric energy, sets the detection period, retrieves the actual electric energy consumed by the equipment within the period, calculates the difference between the actual electric energy consumed by the equipment and the predicted electric energy, when the electric energy difference is less than the threshold, the equipment is marked as normal equipment, when the electric energy difference is greater than the threshold, retrieves the actual voltage and current of the equipment, if the difference between the actual voltage and current of the equipment and the current and voltage in the database is less than the threshold, the equipment is marked as faulty, otherwise it is marked as a transmission line fault, and the management personnel are notified to perform maintenance.

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