Smart park energy consumption management system and method based on Internet of Things

Abstract

The invention relates to the field of energy consumption management, in particular to a smart park energy consumption management system and method based on the Internet of Things. The method comprises the following steps: acquiring power consumption behavior data, user data and power consumption time data of a smart park, and constructing a park power consumption portrait model and a factory power consumption portrait model; according to the park electricity consumption portrait model and the factory electricity consumption portrait model, obtaining behavior characteristic data, a park management value and a production group electricity consumption portrait model; obtaining behavior characteristic data and production equipment data through the production group power consumption portrait model, constructing a production flow line, obtaining production slices and a production management value according to the production group power consumption portrait model and the behavior characteristic data, and obtaining an equipment management coefficient according to the production flow line, the park management value and the production management value; and performing energy consumption management on the factory area in the park according to the production slices and the production management coefficient. The energy utilization rate can be improved.

Description

Technical Field

[0001] The present invention relates to the field of energy consumption management, and particularly to an energy consumption management system and method for intelligent parks based on the Internet of Things. Background Art

[0002] With the acceleration of the industrialization and urbanization processes, parks (especially industrial parks, science and technology parks, etc.) have become major energy consumers; currently, the world is facing problems such as energy shortages and environmental pollution, and energy conservation, emission reduction, and green development have become important directions; the Internet of Things, as a key technology for realizing the interconnection of all things, its core lies in perceiving, identifying, and managing the physical world through various sensors, communication networks, and platforms; in intelligent parks, the Internet of Things provides technical support for the real-time collection, remote monitoring, and intelligent control of energy consumption data, and becomes the basis for constructing an energy efficiency management system.

[0003] In the prior art, refined energy consumption management has not been carried out in the factory areas within the park. For the overall energy consumption management of the park, the impact of the energy consumption in the factory areas on the park's energy consumption is often ignored; the relationship between the equipment production situation and production processes in the factory areas and the energy consumption in the factory areas, and how to manage the energy consumption in the factory areas within the park are problems that need to be solved. Summary of the Invention

[0004] The object of the present invention is to propose an energy consumption management method for intelligent parks based on the Internet of Things in view of the problems in the background art.

[0005] The technical solution of the present invention: An energy consumption management method for intelligent parks based on the Internet of Things includes the following steps: S1. Obtain the electricity consumption behavior data, user data, and electricity consumption time data of the intelligent park, and construct a park electricity consumption portrait model and a factory electricity consumption portrait model according to the electricity consumption behavior data and the electricity consumption time data; S2. Analyze the park electricity consumption portrait model and the factory electricity consumption portrait model to obtain behavior characteristic data, park management values, and a production group electricity consumption portrait model; S3. Through the production group electricity consumption portrait model, obtain behavior characteristic data and production equipment data, construct a production process line, obtain production slices and production management values according to the production group electricity consumption portrait model and the behavior characteristic data, and obtain equipment management coefficients according to the production process line, the park management values, and the production management values; S4. Obtain high-production management slices and low-production management slices according to the production slices and the production management coefficients, and perform energy consumption management on the factory areas within the park to generate an energy consumption management strategy.

[0006] Preferably, the process of obtaining the electricity consumption behavior data, user data, and electricity consumption time data of the smart park and constructing the park electricity consumption portrait model and the factory electricity consumption portrait model based on the electricity consumption behavior data and the electricity consumption time data includes: The smart park includes a factory area and a non-factory area; power monitoring points are set on each power consumption circuit in the distribution room of the smart park and on the user-side distribution box to obtain the electricity consumption behavior data, user data, and electricity consumption time data in the smart sub-park; the electricity consumption behavior data includes the circuit electricity consumption voltage, circuit electricity consumption current, electricity consumption load, and electricity consumption; the electricity consumption time data includes the electricity consumption time and the area label; the area label includes the factory label and the non-factory label; the user data includes user information, the user distribution box relationship, and the distribution box circuit relationship. Set the circuit load label for each power consumption circuit; based on the circuit electricity consumption voltage, circuit electricity consumption current, electricity consumption load, electricity consumption, and electricity consumption time data of the electricity consumption behavior data, construct the electricity consumption voltage change curve, electricity consumption current change curve, electricity consumption load change curve, and electricity consumption change curve respectively. According to the user distribution box relationship and the distribution box circuit relationship, associate the electricity consumption voltage change curve, electricity consumption current change curve, electricity consumption load change curve, and electricity consumption change curve with the user information of the end user to construct the park electricity consumption portrait model, and record the park electricity consumption portrait model containing the factory label as the factory electricity consumption portrait model.

[0007] Preferably, the process of analyzing the park electricity consumption portrait model to obtain the behavior characteristic data and the park management value includes: Based on time series analysis, according to the electricity consumption load change curve and the electricity consumption change curve of the park electricity consumption portrait model, obtain the periodic component and the peak-valley component, obtain the electricity consumption load periodic value and the electricity consumption periodic value of the periodic component and the corresponding electricity consumption load peak value, electricity consumption load valley value, electricity consumption peak value, electricity consumption valley value, and electricity consumption time of the peak-valley component, and record them as the behavior characteristic data; obtain the behavior characteristic data of the park electricity consumption portrait model according to the circuit load label, process the obtained behavior characteristic data by the clustering method, classify the park electricity consumption portrait model, obtain the park type electricity consumption portrait model, and obtain the park group area according to the park area corresponding to the park type electricity consumption portrait model. Obtain the park management value of the park group area according to the behavior characteristic data of the park type electricity consumption portrait model.

[0008] Preferably, the process of analyzing the factory electricity consumption portrait model to obtain the production group electricity consumption portrait model is: Extract and classify the characteristics of the power consumption change curves of all factory power consumption portrait models for each park - type power consumption portrait model. The process of the characteristic extraction and classification is as follows: Set a characteristic window, which is used to identify and extract the power characteristics of the input power consumption change curve. The power characteristics include the power consumption cycle and the power consumption change points, and obtain the change rate according to the power consumption cycle and the power consumption change points, and set the classification change rate; Analyze the change rate and the classification change rate to obtain the power - synchronous points; Obtain the synchronous value according to the power - synchronous points' power - consumption time and the total power - consumption time of the power consumption change curve; Set the synchronous classification interval, and analyze the synchronous classification interval and the synchronous value to obtain the factory - group - type power consumption portrait model; Obtain the total factory power consumption value according to the power consumption of the power consumption change curves of each factory - group - type power consumption portrait model, and record the factory - group - type power consumption portrait model corresponding to the largest total factory - group power consumption value as the production - group power consumption portrait model.

[0009] Preferably, through the production - group power consumption portrait model, obtaining the behavior characteristic data and the production equipment data, the process of constructing the production process line includes: Obtain the behavior characteristic data of the production - group power consumption portrait model, denoted as equipment behavior data. The equipment behavior data includes the equipment power - consumption load cycle value, the equipment power - consumption cycle value, the equipment power - consumption load peak value, the equipment power - consumption load valley value, the equipment power - consumption peak value, the equipment power - consumption valley value, and the equipment power - consumption time; Obtain the production equipment data corresponding to the power - consumption time; The production equipment data includes the production process, the operation cycle, and the material demand; The production process includes the production task, the production time interval, and the production equipment; Obtain the production nodes and the process edges according to the production task and the production equipment, and obtain the production process line according to the production nodes, the process edges, and the material demand; When the equipment power - consumption cycle value or the equipment power - consumption load cycle value is equal to the operation cycle, associate the power - consumption change curve corresponding to the equipment power - consumption cycle value or the power - consumption load change curve corresponding to the equipment power - consumption load cycle value to the production node corresponding to the operation cycle; Set the load evaluation interval.

[0010] Preferably, according to the production - group power consumption portrait model and the behavior characteristic data, obtaining the production slice and the production management value, and the process of obtaining the equipment management coefficient according to the production process line, the park management value, and the production management value includes: Perform production energy consumption analysis on the power consumption load change curve and power consumption change curve of each production node. The production energy consumption analysis process is as follows: Based on the period of the power consumption load change curve, analyze the power consumption load and the load evaluation interval to obtain normal production slices, low production slices, low abnormal production slices, high production slices, and high abnormal production slices; Through the normal production slices, low production slices, low abnormal production slices, high production slices, and high abnormal production slices, obtain normal production power, low production power, low abnormal power, high production power, and high abnormal power. Denote the normal production slices, low production slices, low abnormal production slices, high production slices, and high abnormal production slices as production slices. Analyze the production process line to obtain the production management value of the factory area. Obtain the equipment management value based on the production process line, park management value, and production management value; Obtain the equipment management coefficient based on each equipment management value.

[0011] Preferably, the process of obtaining high production management slices and low production management slices based on production slices and production management coefficients and performing energy consumption management on the factory areas in the park to generate an energy consumption management strategy includes: Set the maximum operating cycle in the factory area as the energy consumption management cycle. Based on the production management coefficient and the energy consumption management cycle, obtain the production management cycle of the production equipment. Based on the low production slices and high production slices of the production equipment, obtain the production ratio. Obtain high production management slices and low production management slices based on the production management cycle, production ratio, low production slices, and high production slices. Align the low production management slices of multiple production equipment and the high production management slices of multiple production equipment in a staggered manner. The staggered alignment means that the time periods of the low production management slices of different production equipment are aligned with the time of the high production management slices of different production equipment, and set the total standard power value; Ensure that the time periods of the low production management slices are consistent with the time periods of the high production management slices, and the sum of the total low production power values of the low production management slices and the total high production power values of the high production management slices is consistent with the total standard power value. Manage the production time of the production equipment through the high production management slices and low production management slices to obtain the energy consumption management strategy.

[0012] The present invention also discloses an intelligent park energy consumption management system based on the Internet of Things, including a management center, which is communicatively connected to a data acquisition module, a data analysis module, a data processing module, and an energy consumption management module: The data acquisition module is used to obtain the power consumption behavior data, user data, and power consumption time data of the intelligent park, and construct a park power consumption portrait model and a factory power consumption portrait model based on the power consumption behavior data and the power consumption time data. The data analysis module is used to analyze the power consumption portrait models of the park and the factory, obtain behavior characteristic data, park management values, and the power consumption portrait model of the production group; The data processing module is used to obtain behavior characteristic data and production equipment data through the power consumption portrait model of the production group, construct a production process line, obtain production slices and production management values according to the power consumption portrait model of the production group and the behavior characteristic data, and obtain equipment management coefficients according to the production process line, park management values, and production management values; The energy consumption management module is used to obtain high-production management slices and low-production management slices according to the production slices and production management coefficients, and perform energy consumption management on the factory areas in the park to generate energy consumption management strategies.

[0013] Compared with the prior art, the above technical solutions of the present invention have the following beneficial technical effects: By constructing the power consumption portrait models of the park and the factory, the comprehensiveness of understanding the power consumption situation of the overall park and the factory areas is improved; with the help of the power consumption portrait models of the park and the factory, behavior characteristic data, park management values, and the power consumption portrait model of the production group are obtained, and the refined analysis ability of the park is improved, which helps to perform block management and analysis on each area of the park; Through the production process line, the relationship between production and energy consumption is analyzed and associated to improve the energy consumption efficiency; with the help of production slices, the production time of production equipment is managed and controlled, and the equipment management coefficient helps to perform combined management on the energy consumption of production equipment; with the help of high-production management slices and low-production management slices, and energy consumption management is performed on the factory areas in the park to improve the fineness and flexibility of energy management. Description of the Drawings

[0014] Figure 1 It is a flowchart of an embodiment proposed by the present invention. Detailed Embodiment

[0015] Embodiment 1, as Figure 1 shown, the intelligent park energy consumption management method based on the Internet of Things proposed by the present invention includes the following steps: S1. Obtain the power consumption behavior data, user data, and power consumption time data of the intelligent park, and construct the power consumption portrait models of the park and the factory according to the power consumption behavior data and the power consumption time data; S2. Analyze the power consumption portrait models of the park and the factory to obtain behavior characteristic data, park management values, and the power consumption portrait model of the production group; S3. Obtain behavioral characteristic data and production equipment data through the production group power consumption portrait model, construct a production process line, obtain production slices and production management values according to the production group power consumption portrait model and the behavioral characteristic data, and obtain equipment management coefficients according to the production process line, park management values and production management values; S4. Obtain high-production management slices and low-production management slices according to the production slices and production management coefficients, and perform energy consumption management on the factory areas in the park to generate energy consumption management strategies.

[0016] It should be further noted that in the specific implementation process, the process of obtaining the power consumption behavior data, user data and power consumption time data of the smart park and constructing the park power consumption portrait model and the factory power consumption portrait model is as follows: The smart park includes factory areas and non-factory areas; power monitoring points are set, and the power monitoring points are set in each power consumption circuit in the distribution room of the smart park and in the user-side distribution boxes, and are used to obtain the power consumption behavior data, user data and power consumption time data in the smart sub-park. The power monitoring points are equipped with Internet of Things devices, including meters, multifunctional meters, sensors, etc.; The power consumption behavior data includes loop power consumption voltage, loop power consumption current, power consumption load and power consumption; The power consumption time data includes power consumption time and area labels; the area labels include factory labels and non-factory labels. When the power monitoring point obtains data of the factory area or non-factory area, the factory label or non-factory label is marked during the power consumption time; The user data includes user information, user distribution box relationship and distribution box loop relationship; the user information includes basic information such as user name, address, power consumption account, etc.; the user distribution box relationship refers to the power distribution relationship between the end user and the user-side distribution box; the distribution box loop relationship refers to the transmission relationship between the user-side distribution box and the loop; Set up an Internet of Things center; upload the obtained power consumption behavior data, user data and power consumption time data to the Internet of Things center, and clean, transform and aggregate the power consumption behavior data, user data and power consumption time data through data processing technology; Set the loop load label for each power consumption loop, and store the power consumption load and power consumption time of each power consumption loop in the corresponding load label; Construct a power consumption voltage change curve, a power consumption current change curve, a power consumption load change curve and a power consumption change curve respectively according to the loop power consumption voltage, loop power consumption current, power consumption load, power consumption and power consumption time data of the power consumption behavior data; According to the relationship between the user's electrical box and the electrical box circuit, the curves of the electrical voltage change, electrical current change, electrical load change, and electrical energy consumption change corresponding to the electrical behavior data and electrical time data are associated with the user information of the end user, and a park electricity consumption portrait model is constructed. The park electricity consumption portrait model containing the factory label is denoted as the factory electricity consumption portrait model.

[0017] It should be further noted that in the specific implementation process, the process of analyzing the park electricity consumption portrait model and the factory electricity consumption portrait model to obtain the behavior characteristic data, park management value, and production group electricity consumption portrait model is as follows: Based on time series analysis, the electrical load change curve and electrical energy consumption change curve of the park electricity consumption portrait model are processed to obtain the periodic component and the peak-valley component, and the electrical load period value and electrical energy consumption period value of the periodic component and the electrical load peak value, electrical load valley value, electrical energy consumption peak value, electrical energy consumption valley value, and electrical time corresponding to the peak-valley component are obtained and denoted as the behavior characteristic data; the behavior characteristic data of the park electricity consumption portrait model is obtained through the loop load label, and the obtained behavior characteristic data is processed by the clustering method, and the park electricity consumption portrait model is classified to obtain the park type electricity consumption portrait model, and the park area corresponding to the park type electricity consumption portrait model is divided into a group, denoted as the park group area; According to the behavior characteristic data of the park type electricity consumption portrait model, the park management value of the park group area is obtained; ; Among them, is the park management value of the park group area numbered u; a is the number of park electricity consumption portrait models in the park group area; is the number of the electrical energy consumption peak values of each park electricity consumption portrait model; The number of the electrical energy consumption valley values of each park electricity consumption portrait model; is the electrical energy consumption period value of each park electricity consumption portrait model; Feature extraction and classification are performed on the power consumption change curves of all factory power consumption portrait models in each park - type power consumption portrait model. The process of the feature extraction and classification is as follows: Set a feature window, which is used to identify and extract the power features of the input power consumption change curve. The power features include the power consumption cycle and the power consumption change points, and calculate the change rate between adjacent power consumption change points in each power consumption cycle. Set a classification change rate; when the change rate between adjacent power consumption change points is less than or equal to the classification change rate, the adjacent power consumption change points are recorded as power - consumption synchronous points; calculate the ratio of the corresponding time interval of the power - consumption synchronous points to the total power - consumption time interval of the power consumption change curve to obtain a synchronous value; set a synchronous classification interval, which includes a classification upper - limit interval and a classification lower - limit interval. If the maximum difference and the minimum difference among multiple synchronous values belong to the synchronous classification interval, the power consumption portraits corresponding to the synchronous values are grouped together and recorded as factory - group - type power consumption portrait models. Calculate the sum of the power consumption of the power consumption change curves of each factory - group - type power consumption portrait model, which is recorded as the total factory power consumption value. The factory - group - type power consumption portrait model corresponding to the largest total factory - group power consumption value is recorded as the production - group power consumption portrait model.

[0018] It should be further noted that in the specific implementation process, through the production - group power consumption portrait model, behavior characteristic data and production equipment data are obtained to construct a production process line. According to the production - group power consumption portrait model and the behavior characteristic data, production slices and production management values are obtained. The process of obtaining the equipment management coefficient according to the production process line, park management value and production management value is as follows: Obtain the behavior characteristic data of the production - group power consumption portrait model, which is recorded as equipment behavior data. The equipment behavior data includes the equipment power - consumption load cycle value, the equipment power - consumption cycle value, the equipment power - consumption load peak value, the equipment power - consumption load valley value, the equipment power - consumption peak value, the equipment power - consumption valley value and the equipment power - consumption time. Obtain the production equipment data corresponding to the power - consumption time; the production equipment data includes the production process, the operation cycle and the material demand; the production process includes production tasks, production time intervals and production equipment; divide the factory area in the smart park, and according to the production tasks and production equipment, record the production equipment as production nodes, record the production tasks as process edges, link the production nodes corresponding to the production equipment in the production process through the process edges corresponding to the production tasks, and store the material demand in the corresponding production nodes to obtain a production process line. When the equipment power consumption cycle value or the equipment power load cycle value is equal to the operation cycle, associate the power consumption change curve corresponding to the equipment power consumption cycle value or the power load change curve corresponding to the equipment power load cycle value with the production node corresponding to the operation cycle; set a load evaluation interval, where the load evaluation interval includes a load evaluation upper limit value and a load evaluation lower limit value; the load evaluation upper limit value is the peak value of the equipment power load, and the load evaluation lower limit value is the valley value of the equipment power load; Conduct production energy consumption analysis on the power load change curve and the power consumption change curve of each production node. The production energy consumption analysis process is as follows: Based on the cycle of the power load change curve, when the power load belongs to the load evaluation interval, record the power consumption time period corresponding to the power load as a normal production slice; when the power load is equal to the load evaluation lower limit value, record the power consumption time period corresponding to the power load as a low production slice; when the power load is less than the load evaluation lower limit value, record the power consumption time period corresponding to the power load as a low abnormal production slice; when the power load is equal to the load evaluation upper limit value, record the power consumption time period corresponding to the power load as a high production slice; when the power load is greater than the load evaluation upper limit value, record the power consumption time period corresponding to the power load as a high abnormal production slice; Through the normal production slice, low production slice, low abnormal production slice, high production slice, and high abnormal production slice, calculate the cumulative power consumption of each production slice within the power consumption change curve to obtain the normal production power, low production power, low abnormal power, high production power, and high abnormal power, and store them in the corresponding production slices. The production slices include normal production slices, low production slices, low abnormal production slices, high production slices, and high abnormal production slices; It should be further noted that in the specific implementation process, particularly for the production slices containing flexible loads, by virtue of the "adjust load according to grid demand or price signal" characteristic of the flexible load through deep learning technology, identify the production slices corresponding to the load that can be adjusted according to grid demand or price signal, and record them as flexible load production slices; Analyze the production process line to obtain the production management value of the factory area; ; Among them, is the production management value of the production equipment numbered h in the factory area; is the operation cycle of the production equipment; is the maximum operation cycle within the factory area; is the time value corresponding to the high production slice of the production equipment; is the maximum time value corresponding to the high production slice of the production equipment in the factory area; is the time value corresponding to the low production slice of the production equipment; is the maximum time value corresponding to the low production slice of the production equipment in the factory area; Multiply the park management value of the park group area by the production management value of the factory area corresponding to the park group area to obtain the equipment management value; perform a ratio calculation on each equipment management value to obtain the production ratio corresponding to the equipment, denoted as the equipment management coefficient.

[0019] It should be further noted that in the specific implementation process, according to the production slices and the production management coefficients, high-production-management slices and low-production-management slices are obtained, and the process of performing energy consumption management on the factory areas in the park and generating the energy consumption management strategy is as follows: Set the maximum operating cycle in the factory area as the energy consumption management cycle, multiply the production management coefficient by the energy consumption management cycle to obtain the production management cycle of the production equipment, and perform a ratio calculation on the corresponding time intervals of the low-production slices and high-production slices of the production equipment to obtain the production ratio; Perform a proportion allocation on the production ratio through the production management cycle, change the time intervals within the low-production slices and high-production slices according to the obtained proportion allocation results to obtain high-production-management slices and low-production-management slices, stagger-align the low-production-management slices of multiple production equipment with the high-production-management slices of multiple production equipment. The stagger alignment means that the time periods of the low-production-management slices of different production equipment are aligned with the time of the high-production-management slices of different production equipment, and set the total standard power value; ensure that the time periods of the low-production-management slices are consistent with those of the high-production-management slices, and the sum of the total low-production power values of the low-production-management slices and the total high-production power values of the high-production-management slices is consistent with the total standard power value. Manage the production time of the production equipment through the high-production-management slices and low-production-management slices to obtain the energy consumption management strategy, and send the low-abnormal production slices and high-abnormal production slices to the production equipment repair personnel for production equipment fault inspection, repair the production equipment, and monitor the real-time production process of the factory area through the production line. If it is inconsistent with the production equipment data in the production line, update the production line, re-perform energy consumption management, and upload the energy consumption management strategy to the Internet of Things to regulate the production time of the production equipment through the Internet of Things; It should be further noted that in the specific implementation process, particularly, the above process is applicable to flexible load production slices, and through the above process, energy consumption management of flexible loads can be achieved.

[0020] Embodiment 2. The intelligent park energy consumption management system based on the Internet of Things proposed in the present invention is applied to the intelligent park energy consumption management method described in Embodiment 1, and specifically includes a management center, which is communicatively connected to a data acquisition module, a data analysis module, a data processing module, and an energy consumption management module: The data acquisition module is used to obtain the electricity consumption behavior data, user data and electricity consumption time data of the smart park, and construct the park electricity consumption portrait model and the factory electricity consumption portrait model according to the electricity consumption behavior data and the electricity consumption time data; The data analysis module is used to analyze the park electricity consumption portrait model and the factory electricity consumption portrait model to obtain the behavior characteristic data, the park management value and the production group electricity consumption portrait model; The data processing module is used to obtain the behavior characteristic data and the production equipment data through the production group electricity consumption portrait model, construct the production process line, obtain the production slice and the production management value according to the production group electricity consumption portrait model and the behavior characteristic data, and obtain the equipment management coefficient according to the production process line, the park management value and the production management value; The energy consumption management module is used to obtain the high production management slice and the low production management slice according to the production slice and the production management coefficient, and perform energy consumption management on the factory areas in the park to generate an energy consumption management strategy.

[0021] The embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. However, the present invention is not limited to this. Various changes can be made without departing from the spirit of the present invention within the knowledge scope of those skilled in the art to which the present invention pertains.

Claims

1. An energy consumption management method for intelligent parks based on the Internet of Things, characterized in that, It includes the following steps: S1. Obtain the electricity consumption behavior data, user data, and electricity consumption time data of the smart park. According to the electricity consumption behavior data and the electricity consumption time data, construct a park electricity consumption portrait model and a factory electricity consumption portrait model; S2. Analyze the park electricity consumption portrait model and the factory electricity consumption portrait model to obtain behavior characteristic data, park management values, and a production group electricity consumption portrait model; S3. Through the production group electricity consumption portrait model, obtain behavior characteristic data and production equipment data, construct a production process line. According to the production group electricity consumption portrait model and the behavior characteristic data, obtain production slices and production management values. According to the production process line, park management values, and production management values, obtain equipment management coefficients; S4. According to the production slices and production management coefficients, obtain high-production management slices and low-production management slices, and perform energy consumption management on the factory areas in the park to generate energy consumption management strategies.

2. The method for energy consumption management of an intelligent park based on the Internet of Things according to claim 1, characterized in that, The process of obtaining the electricity consumption behavior data, user data, and electricity consumption time data of the smart park and constructing a park electricity consumption portrait model and a factory electricity consumption portrait model according to the electricity consumption behavior data and the electricity consumption time data includes: The smart park includes a factory area and a non-factory area; power monitoring points are set in each electricity consumption circuit in the distribution room of the smart park and in the user-side distribution box, and are used to obtain the electricity consumption behavior data, user data, and electricity consumption time data in the smart sub-park; the electricity consumption behavior data includes loop electricity consumption voltage, loop electricity consumption current, electricity consumption load, and electricity consumption; the electricity consumption time data includes electricity consumption time and area labels; the area labels include factory labels and non-factory labels; the user data includes user information, user distribution box relationship, and distribution box circuit relationship; Set the loop load labels for each electricity consumption circuit; according to the loop electricity consumption voltage, loop electricity consumption current, electricity consumption load, electricity consumption, and electricity consumption time data of the electricity consumption behavior data, respectively construct an electricity consumption voltage change curve, an electricity consumption current change curve, an electricity consumption load change curve, and an electricity consumption change curve; According to the user distribution box relationship and the distribution box circuit relationship, associate the electricity consumption voltage change curve, the electricity consumption current change curve, the electricity consumption load change curve, and the electricity consumption change curve with the user information of the terminal user to construct a park electricity consumption portrait model, and record the park electricity consumption portrait model containing factory labels as the factory electricity consumption portrait model.

3. The energy consumption management method for an intelligent park based on the Internet of Things according to claim 2, wherein The process of analyzing the park electricity consumption portrait model to obtain behavior characteristic data and park management values includes: Based on time series analysis, according to the electricity load change curve and electricity consumption change curve of the park electricity consumption portrait model, the periodic component and peak-valley component are obtained. The electricity load periodic value and electricity consumption periodic value of the periodic component, as well as the electricity load peak value, electricity load valley value, electricity consumption peak value, electricity consumption valley value, and electricity consumption time corresponding to the peak-valley component are obtained and recorded as behavior characteristic data. According to the loop load label, the behavior characteristic data of the park electricity consumption portrait model is obtained, and the obtained behavior characteristic data is processed by a clustering method to classify the park electricity consumption portrait model, and a park category electricity consumption portrait model is obtained. According to the park area corresponding to the park category electricity consumption portrait model, the park group area is obtained. Based on the behavior characteristic data of the park category electricity consumption portrait model, the park management value of the park group area is obtained.

4. The method for energy consumption management of an intelligent park based on the Internet of Things according to claim 3, wherein The process of analyzing the factory electricity consumption portrait model to obtain the production group electricity consumption portrait model is as follows: Feature extraction and classification are performed on the electricity consumption change curves of all factory electricity consumption portrait models of each park category electricity consumption portrait model. The process of the feature extraction and classification is as follows: A feature window is set, and the feature window is used to identify and extract the electricity features of the input electricity consumption change curve. The electricity features include the electricity consumption period and the electricity consumption change point, and the change rate is obtained according to the electricity consumption period and the electricity consumption change point, and the classification change rate is set. The change rate and the classification change rate are analyzed to obtain the electricity consumption co-frequency points. According to the electricity consumption time of the electricity consumption co-frequency points and the total electricity consumption time of the electricity consumption change curve, the co-frequency value is obtained. A co-frequency classification interval is set, and the co-frequency classification interval and the co-frequency value are analyzed to obtain the factory group category electricity consumption portrait model. According to the electricity consumption of the electricity consumption change curve of each factory group category electricity consumption portrait model, the total factory electricity consumption value is obtained, and the factory group category electricity consumption portrait model corresponding to the largest total factory group electricity consumption value is recorded as the production group electricity consumption portrait model.

5. The method for energy consumption management of an intelligent park based on the Internet of Things according to claim 4, characterized in that, Through the production group electricity consumption portrait model, obtaining the behavior characteristic data and production equipment data, the process of constructing the production process line includes: Obtain the behavior characteristic data of the production group electricity consumption portrait model, denoted as equipment behavior data. The equipment behavior data includes the equipment electricity load periodic value, equipment electricity consumption periodic value, equipment electricity load peak value, equipment electricity load valley value, equipment electricity consumption peak value, equipment electricity consumption valley value, and equipment electricity consumption time. Obtain the production equipment data corresponding to the electricity consumption time. The production equipment data includes the production process, operation cycle, and material demand. The production process includes production tasks, production time intervals, and production equipment. According to the production tasks and production equipment, production nodes and process edges are obtained. According to the production nodes, process edges, and material demand, the production process line is obtained. When the equipment electricity consumption periodic value or the equipment electricity load periodic value is equal to the operation cycle, the electricity consumption change curve corresponding to the equipment electricity consumption periodic value or the electricity load change curve corresponding to the equipment electricity load periodic value is associated with the production node corresponding to the operation cycle; a load evaluation interval is set.

6. The method for energy consumption management of an intelligent park based on the Internet of Things according to claim 1 or 5, characterized in that Based on the electricity consumption portrait model of the production group and the behavioral characteristic data, obtaining production slices and production management values, and the process of obtaining the equipment management coefficient according to the production process line, the park management value, and the production management value includes: Conducting production energy consumption analysis on the electricity load change curve and the electricity consumption change curve of each production node. The production energy consumption analysis process is as follows: Based on the period of the electricity load change curve, analyzing the electricity load and the load evaluation interval to obtain normal production slices, low production slices, low abnormal production slices, high production slices, and high abnormal production slices; obtaining normal production electricity, low production electricity, low abnormal electricity, high production electricity, and high abnormal electricity through the normal production slices, low production slices, low abnormal production slices, high production slices, and high abnormal production slices, and recording the normal production slices, low production slices, low abnormal production slices, high production slices, and high abnormal production slices as production slices; Analyzing the production process line to obtain the production management value of the factory area; Obtaining the equipment management value according to the production process line, the park management value, and the production management value; obtaining the equipment management coefficient according to each equipment management value.

7. The energy consumption management method for an intelligent park based on the Internet of Things according to claim 6, wherein The process of obtaining high production management slices and low production management slices according to the production slices and the equipment management coefficient, and performing energy consumption management on the factory areas in the park to generate an energy consumption management strategy includes: Setting the maximum operation period in the factory area as the energy consumption management period, obtaining the production management period of the production equipment according to the production management coefficient and the energy consumption management period, and obtaining the production ratio according to the low production slices and high production slices of the production equipment; Obtaining high production management slices and low production management slices according to the production management period, the production ratio, the low production slices, and the high production slices, and staggering and aligning the low production management slices of multiple production equipment with the high production management slices of multiple production equipment. The staggering alignment means that the time periods of the low production management slices of different production equipment are aligned with the time of the high production management slices of different production equipment, and setting the total standard electricity value; ensuring that the time periods of the low production management slices are consistent with the time periods of the high production management slices, and the sum of the total low production electricity values of the low production management slices and the total high production electricity values of the high production management slices is consistent with the total standard electricity value, and managing the production time of the production equipment through the high production management slices and the low production management slices to obtain an energy consumption management strategy.

8. The energy consumption management system for an intelligent park based on the Internet of Things is specifically applied to the energy consumption management method for an intelligent park based on the Internet of Things according to any one of claims 1 to 7, and includes a management center, characterized in that, The management center is communicatively connected to a data acquisition module, a data analysis module, a data processing module, and an energy consumption management module: The data acquisition module is used to obtain the electricity consumption behavior data, user data, and electricity consumption time data of the smart park, and construct a park electricity consumption portrait model and a factory electricity consumption portrait model according to the electricity consumption behavior data and the electricity consumption time data; The data analysis module is used to analyze the park electricity consumption portrait model and the factory electricity consumption portrait model to obtain behavioral characteristic data, park management values, and the electricity consumption portrait model of the production group; The data processing module is used to obtain behavioral characteristic data and production equipment data through the power consumption portrait model of the production group, construct a production process line, obtain production slices and production management values according to the power consumption portrait model of the production group and the behavioral characteristic data, and obtain equipment management coefficients according to the production process line, park management values and production management values; The energy consumption management module is used to obtain high-production management slices and low-production management slices according to the production slices and production management coefficients, perform energy consumption management on the factory areas in the park, and generate energy consumption management strategies.

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