Street lamp energy consumption metering and optimization control method and system

Abstract

The invention relates to the technical field of road lighting, in particular to a street lamp energy consumption metering and optimal control method and system. The method comprises the following steps: creating regional nodes, carrying out association binding between lamp poles and streets and between street lamps and lamp poles, detecting information change conditions, and updating the regional nodes in real time; collecting equipment operation data of the current area in real time, generating a differential energy consumption optimization strategy and an execution scheme, and executing the strategy and the scheme; the execution effect of the control strategy is monitored in real time, alarm and work order processes are linked, and closed-loop optimization is carried out; the system comprises a regional energy consumption association mapping module, an energy consumption optimization generation module and a control effect monitoring module. Through the above mode, the method of accurate metering and dynamic optimization control of street lamp energy consumption is realized, so that the energy consumption cost is reduced, and the intelligent level of urban street lamp management is improved.

Description

A method and system for metering and optimizing the energy consumption of streetlights Technical Field

[0001] This invention relates to the field of road lighting technology, and in particular to a method and system for measuring and optimizing street light energy consumption. Background Technology

[0002] With the acceleration of urbanization, streetlights, as an important component of urban infrastructure, are constantly expanding in number and coverage, making energy consumption an increasingly prominent issue. Traditional streetlight management methods have the following drawbacks: Ambiguous energy consumption metering: They mostly adopt a regional overall metering method, which cannot accurately count the energy consumption data of individual streetlights or individual areas, making it difficult to identify high-energy-consuming nodes; Limited control methods: They mostly use fixed switching times and brightness, without adjusting for dynamic factors such as traffic flow, weather, and time of day, leading to energy waste.

[0003] In conclusion, it is essential to propose a method that enables accurate metering and dynamic optimization control of street light energy consumption in order to reduce energy costs and improve the level of intelligent management of urban street lights. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for street light energy consumption metering and optimization control, aiming to achieve accurate metering and dynamic optimization control of street light energy consumption, so as to reduce energy costs and improve the level of intelligence in urban street light management.

[0005] To achieve the above objectives, the present invention employs a street light energy consumption metering and optimization control method, comprising the following steps: creating regional nodes, associating and binding light poles with streets and streetlights with light poles, detecting information changes, and updating regional nodes in real time; collecting equipment operation data of the current region in real time, generating differentiated energy consumption optimization strategies and execution plans, and executing them; monitoring the execution effect of the control strategies in real time, linking alarms and work order processes, and performing closed-loop optimization.

[0006] The process of creating regional nodes, associating light poles with streets and streetlights with light poles, detecting information changes, and updating regional nodes in real time involves: sequentially creating hierarchical regional nodes, recording the jurisdiction and geographical coordinates of each node, and building a regional framework for energy consumption statistics; entering the light pole number, name, type, and specific location information, and associating the light pole with the street it belongs to; and under the light pole nodes of the associated streets, associating streetlights with their respective light poles, forming a mapping relationship between region, light pole, and streetlight.

[0007] Among them, after the step of associating and binding streetlights with their respective light poles under the light pole nodes of the associated streets to form a mapping relationship of area-light pole-streetlight: real-time detection of information changes of area, light pole, and streetlight.

[0008] In the step of real-time detection of information changes in areas, light poles, and streetlights: when information changes occur, the mapping relationship is updated synchronously.

[0009] The process of collecting real-time equipment operation data in the current area, generating differentiated energy consumption optimization strategies and implementation plans, and executing them includes: collecting real-time operation data of each street light in the current area; the operation data includes voltage, current, and operating time; summarizing and processing the collected operation data; and generating differentiated energy consumption optimization strategies by combining the current area's energy consumption statistics, regional traffic flow data, and historical energy consumption data.

[0010] In the step of summarizing and processing the collected operational data, energy consumption data is statistically analyzed by region and time period, and the energy consumption distribution is displayed in the form of a bar chart.

[0011] The process involves generating differentiated energy consumption optimization strategies by combining current regional energy consumption statistics, regional traffic flow data, and historical energy consumption data. This includes: associating the target region with the generated energy consumption optimization strategies, setting the execution time for the plan, and then executing it.

[0012] In the process of real-time monitoring of the control strategy execution effect, linking alarms and work order processes, and performing closed-loop optimization: the lighting rate and online rate of streetlights in the current area are monitored in real time, the equipment operation status after the control strategy is executed is queried, and energy consumption comparison reports are generated by area and time period to analyze the changes in energy consumption after the strategy is executed; when energy consumption exceeds the preset threshold, the lighting rate is lower than the set standard, or the equipment is offline, alarm information is generated, the alarm name, type, equipment location and abnormal data are recorded, and an alarm notification is pushed at the same time.

[0013] The process involves generating alarm information, recording the alarm name, type, device location, and abnormal data, and simultaneously pushing an alarm notification when energy consumption exceeds a preset threshold, the lighting rate is lower than the set standard, or the device is offline. Following this, the user can view the alarm information, select a repair department and personnel, associate the repair personnel's contact information, set a repair time, and complete the work assignment. After the repair is completed, the repair personnel upload the cause of the fault, repair steps, and before-and-after photos. Combined with monitoring data and repair records, the system optimizes strategy parameters and performs closed-loop iteration.

[0014] This invention also provides a street light energy consumption metering and optimization control system, including a regional energy consumption association mapping module, an energy consumption optimization generation module, and a control effect monitoring module; wherein: the regional energy consumption association mapping module is used to create regional nodes, associate and bind light poles with streets and streetlights with light poles, detect information changes, and update regional nodes in real time; the energy consumption optimization generation module is used to collect equipment operation data of the current region in real time, generate differentiated energy consumption optimization strategies and execution schemes, and execute them; the control effect monitoring module is used to monitor the execution effect of the control strategy in real time, link alarms and work order processes, and perform closed-loop optimization.

[0015] This invention discloses a method and system for street light energy consumption metering and optimization control. The method comprises a regional energy consumption association mapping module, an energy consumption optimization generation module, and a control effect monitoring module, which perform the following steps: creating regional nodes, associating and binding light poles with streets and streetlights with light poles, detecting information changes, and updating regional nodes in real time; collecting equipment operation data for the current region in real time, generating differentiated energy consumption optimization strategies and execution plans, and executing them; monitoring the execution effect of the control strategies in real time, linking alarms and work order processes, and performing closed-loop optimization; through the above methods, a method for accurate metering and dynamic optimization control of street light energy consumption is achieved, thereby reducing energy costs and improving the intelligent level of urban street light management. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 is a flowchart of the steps of the street light energy consumption metering and optimization control method of the present invention.

[0018] Figure 2 is a flowchart of steps S100 of the present invention.

[0019] Figure 3 is a flowchart of steps S200 of the present invention.

[0020] Figure 4 is a flowchart of steps S300 of the present invention.

[0021] Figure 5 is a schematic diagram of the street light energy consumption metering and optimization control system of the present invention.

[0022] Figure 6 is a schematic diagram of the electronic device of the present invention.

[0023] 401 - Regional energy consumption correlation mapping module, 402 - Energy consumption optimization generation module, 403 - Control effect monitoring module. Detailed Implementation

[0024] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0025] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0026] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0027] Please refer to Figures 1 to 4. The present invention provides a method for metering and optimizing the energy consumption of streetlights, including the following steps: S100: Create regional nodes, associate and bind light poles with streets and streetlights with light poles, detect information changes, and update regional nodes in real time.

[0028] In this implementation, regional nodes are created to associate and bind light poles with streets and streetlights with light poles, and information changes are detected and the regional nodes are updated in real time. The specific process is as follows: S101: Create hierarchical regional nodes sequentially, record the jurisdiction and geographical coordinates of each node, and build a regional framework for energy consumption statistics; S102: Enter the light pole number, name, type, and specific location information, and associate and bind the light pole with the street it belongs to; S103: Under the light pole node of the associated street, associate and bind the streetlight with the light pole it belongs to, forming a mapping relationship of region-light pole-streetlight; S104: Detect information changes of region, light pole, and streetlight in real time, and update the mapping relationship synchronously when information changes occur.

[0029] In the above process, hierarchical regional nodes are created sequentially according to the administrative levels of "province-city-district-street". The geographical coordinates of the jurisdiction boundary and the center point of each node are accurately recorded. This establishes the basic regional framework for energy consumption statistics and ensures that subsequent energy consumption data can be accurately located to specific administrative regions.

[0030] Enter the unique number, custom name, structural type (such as ordinary light pole, intelligent integrated light pole) and detailed description of the specific installation location of each light pole (such as 3 meters northeast of the intersection of XX Street and XX Road) to complete the association and binding of the light pole with the street to which it belongs, so that each light pole has a clear street affiliation.

[0031] Under the street-linked light pole nodes, basic information such as the street light's equipment number, name, model, manufacturer, and installation date is entered to associate and bind the street light with its corresponding light pole, thereby forming a complete three-level mapping relationship of "region-light pole-street light" and achieving precise positioning from the macro-region to the micro-device.

[0032] A timed scanning mechanism is set up to detect changes in information such as area division adjustments, additions or removals of light poles, changes in their positions, replacement of streetlights, or modification of parameters in real time. When a change in information is detected, the mapping relationship update process is automatically triggered, and the associated data is modified synchronously to ensure that the mapping relationship is always consistent with the actual situation.

[0033] S200: Collects real-time equipment operation data in the current area, generates differentiated energy consumption optimization strategies and execution plans, and executes them.

[0034] In this embodiment, real-time equipment operation data for the current area is collected, a differentiated energy consumption optimization strategy and execution plan are generated, and then executed. The specific process is as follows: S201: Real-time collection of operation data for each street light in the current area; the operation data includes voltage, current, and operating time; S202: Summarizing and processing the collected operation data, statistically analyzing energy consumption data by region and time period, and displaying the energy consumption distribution in the form of a bar chart; S203: Combining the current area's energy consumption statistics, regional traffic flow data, and historical energy consumption data, a differentiated energy consumption optimization strategy is generated; S204: Associating the target area with the generated energy consumption optimization strategy, setting the execution time of the plan, and then executing it.

[0035] During the above process, the intelligent sensing device installed on each street light collects the operating data of each street light in the current area in real time at a frequency of once per minute. The operating data includes the operating voltage, operating current and cumulative running time. The collected data is uploaded in real time via power line carrier or wireless communication.

[0036] The uploaded operational data is aggregated and processed, and energy consumption data is statistically analyzed according to different regional levels such as province, city, district, and street, as well as different time periods such as day, week, month, and year. The energy consumption distribution of each region and time period is displayed intuitively in the form of bar charts, which makes it easier for managers to quickly identify high energy consumption areas and time periods.

[0037] The data fusion algorithm is invoked to comprehensively analyze the real-time energy consumption statistics of the current area, the regional traffic density data (such as traffic data during the morning peak from 7:00 to 9:00 and the evening peak from 17:00 to 19:00), and the historical energy consumption data of the same period, and generate differentiated energy consumption optimization strategies that include the street light brightness adjustment level and the switching time of the lights during different time periods (such as off-peak, peak, and late night).

[0038] The generated differentiated energy consumption optimization strategies are associated and bound with the target control area. The execution time of the plan is set according to the characteristics of the area (daily, legal working days, legal holidays or custom time periods can be selected), and the street lights in the target area are controlled according to the strategy.

[0039] S300: Real-time monitoring of the execution effect of control strategies, linkage of alarms and work order processes, and closed-loop optimization.

[0040] In this implementation, the execution effect of the control strategy is monitored in real time, and alarms and work orders are linked to perform closed-loop optimization. The specific process is as follows: S301: Monitor the lighting rate and online rate of streetlights in the current area in real time, query the equipment operation status after the control strategy is executed, and generate energy consumption comparison reports by area and time period to analyze the changes in energy consumption after the strategy is executed; S302: When energy consumption exceeds the preset threshold, the lighting rate is lower than the set standard, or equipment is offline, generate alarm information, record the alarm name, type, equipment location and abnormal data, and push alarm notification; S303: View the alarm information, select the maintenance department and maintenance personnel, associate the maintenance personnel's contact information, set the maintenance time and complete the work assignment; S304: After the maintenance is completed, the maintenance personnel upload the cause of the fault, maintenance steps, and before and after photos of the maintenance. Combine the monitoring data and maintenance records to optimize the strategy parameters and perform closed-loop iteration.

[0041] During the above process, key indicators such as the lighting rate of streetlights and the online rate of equipment in the current area are displayed in real time, helping managers to intuitively grasp the equipment operation status after the control strategy is implemented; energy consumption comparison reports are automatically generated by region and time period, and by comparing with historical data before the strategy is implemented, the changes in energy consumption after the strategy is implemented are quantitatively analyzed and the energy-saving effect is evaluated.

[0042] When an alarm is detected that the energy consumption of a certain area or a street light exceeds the preset threshold of the average energy consumption of similar equipment, the lighting rate is lower than the set standard of 90%, or the equipment is offline, an alarm message is generated, and the alarm name, fault type, location of occurrence and related abnormal data are recorded in detail and pushed to the terminal device of the management personnel.

[0043] Managers view alarm information, select the corresponding repair department and repair personnel based on the fault type and location, and link the repair personnel's contact information. After setting the deadline for completing the repair, managers assign the work order to the repair personnel, who then receive the work order notification via a mobile app.

[0044] After maintenance personnel arrive at the site and complete the maintenance work, they upload the fault cause analysis, detailed maintenance steps, and before-and-after comparison photos of the site for review. After the management personnel approve the work, they combine energy consumption monitoring data and maintenance records to optimize and adjust the control strategy parameters, forming a closed-loop management process of "monitoring-alarm-maintenance-optimization" to continuously improve the energy consumption control effect.

[0045] In this invention, firstly, regional nodes are created to associate and bind light poles with streets and streetlights with light poles, and information changes are detected to update the regional nodes in real time. Then, the current equipment operation data of the region is collected in real time to generate differentiated energy consumption optimization strategies and execution plans, and these are then executed. Finally, the execution effect of the control strategies is monitored in real time, and alarms and work order processes are linked to perform closed-loop optimization. Through the above methods, a method for accurate metering and dynamic optimization control of streetlight energy consumption is achieved, thereby reducing energy costs and improving the level of intelligence in urban streetlight management.

[0046] Corresponding to the aforementioned embodiments of the street light energy consumption metering and optimization control method, this application also provides embodiments of the street light energy consumption metering and optimization control system.

[0047] Figure 5 is a block diagram of a street light energy consumption metering and optimization control system according to an exemplary embodiment. Referring to Figure 5, the system may include: a regional energy consumption association mapping module 401, an energy consumption optimization generation module 402, and a control effect monitoring module 403; wherein: the regional energy consumption association mapping module 401 is used to create regional nodes, associate and bind light poles with streets and streetlights with light poles, detect information changes, and update regional nodes in real time; the energy consumption optimization generation module 402 is used to collect equipment operation data of the current region in real time, generate differentiated energy consumption optimization strategies and execution schemes, and execute them; the control effect monitoring module 403 is used to monitor the execution effect of the control strategy in real time, link alarms and work order processes, and perform closed-loop optimization.

[0048] In this embodiment, the regional energy consumption association mapping module 401 creates regional nodes, associates and binds light poles with streets and streetlights with light poles, detects information changes, and updates regional nodes in real time; the energy consumption optimization generation module 402 collects equipment operation data of the current region in real time, generates differentiated energy consumption optimization strategies and execution plans, and executes them; the control effect monitoring module 403 monitors the execution effect of the control strategy in real time, links alarms and work order processes, and performs closed-loop optimization; through the above methods, a method for accurate metering and dynamic optimization control of streetlight energy consumption is achieved, so as to reduce energy costs and improve the intelligent level of urban streetlight management.

[0049] Regarding the system in the above embodiments, the specific ways in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0050] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0051] Accordingly, this application also provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the street light energy consumption metering and optimization control method described above. Figure 6 shows a hardware structure diagram of any data processing capability device in which a street light energy consumption metering and optimization control system is located, according to an embodiment of the present invention. Besides the processor, memory, and network interface shown in Figure 6, the data processing capability device in the embodiment may also include other hardware depending on the actual function of the data processing capability device, which will not be elaborated further.

[0052] Accordingly, this application also provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the street light energy consumption metering and optimization control method described above. The computer-readable storage medium can be an internal storage unit of any data processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data processing device, and can also be used to temporarily store data that has been output or will be output.

[0053] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0054] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for metering and optimizing the energy consumption of streetlights, characterized in that, The process includes the following steps: creating regional nodes, associating and binding light poles with streets and streetlights with light poles, detecting information changes, and updating regional nodes in real time; collecting equipment operation data for the current region in real time, generating differentiated energy consumption optimization strategies and implementation plans, and executing them; Real-time monitoring of the execution effect of control strategies, linkage of alarms and work order processes, and closed-loop optimization.

2. The street light energy consumption metering and optimization control method as described in claim 1, characterized in that, The steps for creating regional nodes, associating light poles with streets and streetlights with light poles, detecting information changes, and updating regional nodes in real time are as follows: Hierarchical regional nodes are created sequentially, recording the jurisdiction and geographical coordinates of each node to build a regional framework for energy consumption statistics; light pole numbers, names, types, and specific location information are entered, and light poles are associated with their respective streets; under the light pole nodes of the associated streets, streetlights are associated with their respective light poles, forming a mapping relationship between region, light pole, and streetlight.

3. The street light energy consumption metering and optimization control method as described in claim 2, characterized in that, After linking streetlights to their respective poles and creating a mapping relationship between area, pole, and streetlight, real-time monitoring of changes in area, pole, and streetlight information is performed on the associated streetlight pole nodes.

4. The street light energy consumption metering and optimization control method as described in claim 3, characterized in that, In the process of real-time detection of information changes in areas, light poles, and streetlights: when information changes occur, the mapping relationship is updated synchronously.

5. The street light energy consumption metering and optimization control method as described in claim 1, characterized in that, In the steps of collecting real-time equipment operation data in the current area, generating differentiated energy consumption optimization strategies and execution plans, and executing them: real-time collection of operation data for each street light in the current area; The operational data includes voltage, current, and operating time; the collected operational data is aggregated and processed; and differentiated energy consumption optimization strategies are generated by combining current regional energy consumption statistics, regional traffic flow data, and historical energy consumption data.

6. The street light energy consumption metering and optimization control method as described in claim 5, characterized in that, In the step of summarizing and processing the collected operational data: energy consumption data is statistically analyzed by region and time period, and the energy consumption distribution is displayed in the form of a bar chart.

7. The street light energy consumption metering and optimization control method as described in claim 6, characterized in that, After generating differentiated energy consumption optimization strategies by combining current regional energy consumption statistics, regional traffic flow data, and historical energy consumption data, the following steps are taken: associating the target region with the generated energy consumption optimization strategies, setting the execution time of the plan, and then executing it.

8. The street light energy consumption metering and optimization control method as described in claim 1, characterized in that, In the steps of real-time monitoring of the control strategy execution effect, linking alarms and work order processes, and performing closed-loop optimization: the current area's street light illumination rate and online rate are monitored in real time, the equipment operating status after the control strategy is executed is queried, and energy consumption comparison reports are generated by region and time period to analyze the energy consumption changes after the strategy is executed; when energy consumption exceeds the preset threshold, illumination rate is lower than the set standard, or equipment is offline, alarm information is generated, the alarm name, type, equipment location and abnormal data are recorded, and an alarm notification is pushed at the same time.

9. The street light energy consumption metering and optimization control method as described in claim 8, characterized in that, When energy consumption exceeds the preset threshold, the lighting rate is lower than the set standard, or equipment is offline, an alarm message is generated, recording the alarm name, type, equipment location, and abnormal data. Simultaneously, an alarm notification is pushed. Afterwards, the alarm message is viewed, a repair department and personnel are selected, the repair personnel's contact information is linked, and a repair time is set to complete the work assignment. After repair, the repair personnel upload the cause of the fault, repair steps, and before-and-after photos. Combining the monitoring data and repair records, the strategy parameters are optimized for closed-loop iteration.

10. A street light energy consumption metering and optimization control system, applied to the street light energy consumption metering and optimization control method as described in claim 1, characterized in that, It includes a regional energy consumption association mapping module, an energy consumption optimization generation module, and a control effect monitoring module; wherein: the regional energy consumption association mapping module is used to create regional nodes, associate and bind light poles with streets and streetlights with light poles, detect information changes, and update regional nodes in real time; the energy consumption optimization generation module is used to collect equipment operation data of the current region in real time, generate differentiated energy consumption optimization strategies and execution plans, and execute them; the control effect monitoring module is used to monitor the execution effect of the control strategy in real time, link alarms and work order processes, and perform closed-loop optimization.

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