A method for intelligent control of power load in a park

Abstract

This invention discloses an intelligent control method for industrial park power load, relating to the field of energy utilization technology. Addressing the problem of inability to intelligently control industrial park power load, this solution includes a server, power line control equipment, power quality monitoring equipment, and power line load monitoring equipment. The server uses current and historical external power quality data to perform weighted prediction of power quality trends for subsequent time periods and controls external power lines. The power line control equipment receives real-time switching control commands for external power lines from the server. The power quality monitoring equipment collects and sends multi-dimensional quality data from both external and internal power lines to the server in real time. The power line load monitoring equipment sends internal power line load data to the server in real time. The advantage lies in intelligently controlling the industrial park's power load through pre-allocated lines, dynamic line control, load balancing, and pre-generated production plans, thereby reducing production risks.

Description

Technical Field

[0001] This invention relates to the field of energy utilization technology, and in particular to a method for intelligent control of power load in a park. Background Technology

[0002] Energy supply is a fundamental condition for ensuring the normal production and operation of enterprises. The stability of energy supply directly affects product quality and the economic benefits of enterprises. At present, the information and digital management of industrial parks is still relatively superficial, and the collection of production information is still relatively simple. As for power management, it is still in the stage of reducing the use of power-consuming equipment and the lack of intelligent and automatic power regulation.

[0003] The inability to adjust promptly to fluctuations in external energy supply actually increases equipment energy loss rates. During peak production periods, a significant increase in defect rates, circuit breaker trips, energy consumption, and emissions reduces asset utilization and raises production costs. Furthermore, while managers rely heavily on experience to monitor and evaluate the economics of energy consumption, human factors limit their ability to identify more efficient production methods through comparative energy consumption data. This results in substantial expenditures that fail to meet energy efficiency targets, further increasing customer production costs. Summary of the Invention

[0004] The purpose of this invention is to provide a method for intelligent control of power load in a park, so as to solve the problems existing in the prior art.

[0005] The present invention provides a method for intelligent control of power load in a park, comprising a server, power line control equipment, power quality monitoring equipment, and power line load monitoring equipment.

[0006] The server uses current and historical external power quality data to perform weighted predictions of power quality trends for subsequent time periods and to control external power lines.

[0007] The power line control equipment receives real-time control commands for switching power lines outside the park via a server.

[0008] The power quality monitoring equipment collects and sends multi-dimensional quality data of external and internal power lines to the server in real time.

[0009] The power line load monitoring device sends internal power line load data to the server in real time.

[0010] The server uses historical internal power load data, internal power line temperature and thermal monitoring, and production plans to perform weighted predictions of power load demand and temperature conditions for subsequent periods. Based on the current carbon price, the server estimates the consumption of emission allowances, estimates carbon emission reduction benefits, and provides carbon trading suggestions to ensure that allowances are available while maximizing benefits.

[0011] The power line control equipment switches, merges, turns on, and turns off the internal lines of the park, and feeds back the operation data to the server in real time.

[0012] The internal wiring includes several lines and a power generation system, the power generation system including an uninterruptible power supply and a generator; the external power lines include at least two lines.

[0013] The process includes the following steps: S1: At a pre-set trigger time, the server obtains the necessary parameters for the production plan; S2: The production plan is adjusted based on whether there are power outages scheduled during the production demand period; S3: The server actively obtains current internal and external power line quality data and historical data; S4: The server actively obtains current power line load data, temperature and thermal data, and historical data; S5: Based on the internal power line conditions, the server makes corresponding decisions; S6: The server estimates the consumption of emission allowances based on the current carbon price, estimates carbon reduction profits, and provides carbon trading suggestions to ensure allowance availability while maximizing profits; S7: The server calculates and stores the evaluation production time, production energy consumption, and energy costs; S8: The server analyzes and learns from historical plan completion data and evaluation data, and generates a production plan for the current production demand based on the above data; S9: The server sends the production plan to the Manufacturing Execution System (MES), which then executes it.

[0014] The required parameters for the production plan include production demand, current enterprise emission standards, ongoing production plans, data on plan completion, and power outage arrangements.

[0015] The manufacturing execution system is a "5G production MES" system, which includes management modules such as manufacturing data management, equipment management, tool management, and procurement management, and feeds the management data back to the server.

[0016] Step S2 includes steps S21, S22, and S23; Step S21 includes determining the allocation of power lines within the current production demand period and determining the external power line switching plan when there is no power outage scheduled within the production demand period; Step S22 includes formulating a production plan according to the power generation system situation when there is a power outage scheduled within the production demand period and the outage time is within the existing production plan or when external lines are simultaneously out of power; Step S23 includes continuously generating production plans when there is a power outage scheduled within the production demand period and the outage time is within the existing production plan and external lines are available.

[0017] Step S3 further includes analyzing historical production plans and the situation described in step S2 to generate a production plan that meets current production needs, and calculating and evaluating production time, production energy consumption, and production costs.

[0018] Step S5 includes step S51, where when the quality data of a certain internal power line is lower than the first threshold required for production, while the load data and temperature and thermal data of the other power lines are within a preset range, the server sends an internal power line switching or merging message to the power line control equipment based on the line data and the production plan prediction, to ensure that the power quality of the current production is maintained within the threshold.

[0019] Step S5 includes step S52, in which when the quality data of a certain internal power line is lower than the first threshold required for production, and the load data and temperature thermal data of the other power lines are outside the preset range, the server will issue a warning message to the management personnel and will suspend the allocation of the current line's production plan after the current line's production plan ends.

[0020] The intelligent power load control method for industrial parks described in this invention has the advantages of intelligently controlling the park's power load based on the external power conditions and internal line load conditions at different times. This is achieved through pre-allocation of power lines, dynamic line control, load balancing, and pre-generated production plans. This improves production yield, reduces production risks, increases equipment uptime and energy utilization, and promotes energy conservation and emission reduction in the park. By combining power quality, equipment condition, estimated production costs, and carbon emission trading prices, it achieves optimal production configuration and makes better decisions, improving production efficiency, reducing error rates, increasing production yield, reducing production risks, improving equipment uptime and energy utilization, and lowering enterprise production costs. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of an intelligent control method for park electrical load as described in this invention. Detailed Implementation

[0022] A method for intelligent control of power load in a park includes a server, power line control equipment, power quality monitoring equipment, and power line load monitoring equipment.

[0023] The server uses weighted averages of current and historical external power quality data to predict power quality trends for subsequent time periods and to control external power lines. The server communicates with power line control equipment, power quality monitoring equipment, and power line load monitoring equipment, specifically via a 5G communication interface. Upon reaching a preset time trigger, the server processes collected data from various sources and production data to generate a production plan for a subsequent time period. The server also includes collecting information on power line quality and load, and automatically generating production plans. Specifically, the server acquires data collected by the power quality monitoring equipment.

[0024] The power line control equipment receives real-time control commands for switching external power lines via a server. It can also switch, merge, open, and close internal power lines within the park, and feed the results back to the server in real time.

[0025] The power quality monitoring equipment collects and sends multi-dimensional quality data of external and internal power lines to the server in real time.

[0026] The power line load monitoring equipment transmits internal power line load data to the server in real time. The power line load monitoring equipment includes a temperature monitoring device for monitoring temperature.

[0027] The external power lines include at least two lines. In this embodiment, the external power lines consist of one energy storage line and one backup line. The two lines use different power plants, which ensures high reliability of power supply within the park. The internal power lines include several lines and a power generation system. The power generation system includes an uninterruptible power supply (UPS) and generators. The UPS stores electricity and is always on standby; it will immediately start supplying power after a power outage.

[0028] The intelligent control method for power load in the industrial park includes the following steps: S1: At a pre-set trigger time, the server obtains production demand, the current remaining emission indicators of the enterprise, the currently executing production plan, the planned completion data, and the pre-entered power outage arrangements; S2: Adjust the production plan according to whether there are power outage arrangements during the production demand time.

[0029] S3: The server actively acquires current internal and external power line quality data and historical data; S4: The server actively acquires current power line load data, temperature and thermal data, and historical data; S5: Based on the internal power line conditions, the server makes corresponding decisions; S6: The server estimates the consumption of emission allowances based on the current carbon price, estimates carbon reduction profits, and provides carbon trading suggestions to ensure allowance availability while maximizing profits; S7: The server calculates and stores the assessment of production time, production energy consumption, and energy costs; S8: The server analyzes and learns from historical planned completion data and assessment data, and generates a production plan based on the above data to meet current production needs; S9: The server sends the production plan to the Manufacturing Execution System (MES), which then executes it.

[0030] The "5G Manufacturing Execution System" feeds information back to the server to generate a production plan. In this embodiment, the manufacturing execution system is the "5G Manufacturing Execution System," which includes management modules such as manufacturing data management, quality management, equipment management, tool management, and procurement management, and feeds management data back to the server.

[0031] Step S2 includes steps S21, S22, and S23. Step S21 involves, assuming no power outages are scheduled during the production demand period, the server analyzes external power line quality data stored up to the current trigger point, as well as internal power quality and load data, and weights this data to predict the current production demand line quality, load, and production cost, determining the power line allocation within the current production demand period. If all previously unfulfilled production demands and the currently generated demand do not overlap in time, the server predicts the external line quality. If a switchover is required, after the old production demand ends and before the new production demand begins, the server sends a command to the power line control equipment to switch to a selectable external line. Before the entire production plan ends and the equipment stops operating, external power line switching cannot be performed due to power grid and production safety factors.

[0032] Step S22 includes the following: if there is a power outage scheduled within the production demand and the outage time coincides with an existing production plan or a simultaneous power outage on an external line, the server formulates a production plan based on the power generation system status. If no power generation system is available, the server will suspend and formulate a production plan according to the power outage schedule and the actual power restoration time. Before the generators in the power generation system supply power, the server will configure relevant parameters such as frequency, voltage, phase sequence, and voltage phase to be the same as those of the current line.

[0033] Step S23 includes the following steps: If a power outage is scheduled within the production demand and the outage time is within the existing production plan while external power lines are available, the server will start the power generation system a preset time before the outage time, and determine whether to switch external power lines based on the production demand time and weight. The server will then shut down the power generation system a preset time after power is restored or after production is completed. If no power generation system is available, the server will suspend the production plan and switch power lines.

[0034] Step S3 further includes analyzing historical production plans and the situation described in step S2 to generate a production plan that meets current production needs, and calculating and evaluating production time, production energy consumption, and production costs.

[0035] Step S5 is divided into steps S51 and S52. Step S51 involves the server sending a power line switching or merging command to the power line control equipment when the power quality data of a certain internal power line falls below the first threshold required for production, while the load data and temperature / thermal data of other power lines are within a preset range. This ensures that the power quality of the current production remains within the threshold. Step S52 involves the server issuing a warning message to the management personnel when the power quality data of a certain internal power line falls below the first threshold required for production, while the load data and temperature / thermal data of other power lines are outside the preset range. The server will also suspend the allocation of the current line's production plan after the current line's production plan has ended.

[0036] For those skilled in the art, various other corresponding changes and modifications can be made based on the technical solutions and concepts described above, and all such changes and modifications should fall within the protection scope of the claims of this invention.

Claims

1. A method for intelligent control of power load in a park, characterized in that, This includes servers, power line control equipment, power quality monitoring equipment, and power line load monitoring equipment. The server uses current and historical external power quality data to perform weighted predictions of power quality trends for subsequent time periods and to control external power lines. The power line control equipment receives real-time control commands for switching power lines outside the park via a server. The power quality monitoring equipment collects and sends multi-dimensional quality data of external and internal power lines to the server in real time. The power line load monitoring device sends internal power line load data to the server in real time. The server uses historical internal power load data, internal power line temperature and thermal monitoring, and production plans to perform weighted predictions of power load demand and temperature conditions for subsequent periods. Based on the current carbon price, the server estimates the consumption of emission allowances, estimates carbon emission reduction benefits, and provides carbon trading suggestions to ensure that allowances are available while maximizing benefits. The power line control equipment switches, merges, turns on, and turns off the internal power lines of the park and feeds back the operation data to the server in real time.

2. The intelligent control method for park power load according to claim 1, characterized in that, The internal wiring includes several lines and a power generation system, the power generation system including an uninterruptible power supply and a generator; the external power lines include at least two lines.

3. The intelligent control method for park power load according to claim 2, characterized in that, The process includes the following steps: S1: At a pre-set trigger time, the server obtains the required parameters for the production plan; S2: The production plan is adjusted based on whether there are power outages or other factors during the production demand period. S3: The server actively acquires current internal and external power line quality data as well as historical data; S4: The server actively acquires current power line load data, temperature and thermal data, and historical data; S5: The server makes corresponding decisions based on the internal power line conditions; S6: The server estimates the consumption of emission allowances based on the current carbon price, estimates the carbon emission reduction profit and provides carbon trading suggestions to ensure that allowances are available while maximizing profits. S7: The server calculates and stores assessments of production time, production energy consumption, and energy costs; S8: The server analyzes and learns historical project completion data and evaluation data, and generates a production plan based on the above data to meet current production needs; S9: The server sends the production plan to the Manufacturing Execution System (MES), which then executes it.

4. The intelligent control method for park power load according to claim 3, characterized in that, The required parameters for the production plan include production demand, current remaining emission quotas for the enterprise, ongoing production plans, data on plan completion, and power outage arrangements.

5. The intelligent control method for park power load according to claim 4, characterized in that, The manufacturing execution system is a "5G Manufacturing MES" system, which includes management modules such as manufacturing data management and feeds management data back to the server.

6. The intelligent control method for park power load according to claim 5, characterized in that, Step S2 includes steps S21, S22, and S23; Step S21 includes determining the allocation of power lines within the current production demand period and determining the external power line switching plan when there is no power outage scheduled within the production demand period; Step S22 includes formulating a production plan according to the power generation system situation when there is a power outage scheduled within the production demand period and the outage time is within the existing production plan or when external lines are simultaneously out of power; Step S23 includes continuously generating a production plan when there is a power outage scheduled within the production demand period and the outage time is within the existing production plan and external lines are available.

7. The intelligent control method for park power load according to claim 6, characterized in that, Step S3 further includes analyzing historical production plans and the situation described in step S2 to generate a production plan that meets current production needs, and calculating and evaluating production time, production energy consumption, and production costs.

8. The intelligent control method for park power load according to claim 3, characterized in that, Step S5 includes step S51, where when the quality data of a certain internal power line is lower than the first threshold required for production, while the load data and temperature and thermal data of the other power lines are within a preset range, the server sends an internal power line switching or merging message to the power line control equipment based on the line data and the production plan prediction, to ensure that the power quality of the current production is maintained within the threshold.

9. The intelligent control method for park power load according to claim 8, characterized in that, Step S5 includes step S52, in which when the quality data of a certain internal power line is lower than the first threshold required for production, and the load data and temperature thermal data of the other power lines are outside the preset range, the server will issue a warning message to the management personnel and will suspend the allocation of the current line's production plan after the current line's production plan ends.

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