System and method for intelligent energy management, and computing device

Abstract

Provided in the present invention are a system and method for intelligent energy management and a computing device, which are used for energy data management. The system is a four-level architecture, and comprises a first level, a second level, a third level and a fourth level. The first level is responsible for data storage, processing and analysis; the second level uses a data transmission method to perform data transmission between the first level and a third level; the third level performs data transmission with the second level by means of an uplink communication interface, uses an edge computing apparatus to perform energy data computation and management, and performs data transmission with the fourth level by means of a downlink communication interface; by means of an energy monitoring terminal, the fourth level performs data collection. The technical solution of the present invention can have relatively strong compatibility and scalability, update monitoring data in real time, improve the energy management and control level, significantly improve user experience, implement rapid fault locating and recovery, optimize resource configurations, save costs and reduce energy consumption.

Description

Systems and methods for intelligent energy management and computing devices Technical Field

[0001] This invention relates to the field of software development, and more specifically to a system, method, and computing device for intelligent energy management. Background Technology

[0002] Smart grids represent the future direction of power system development. Smart grids require comprehensive monitoring, control, and management of the power system to improve its reliability, security, and efficiency. As a crucial component of smart grids, energy systems enable remote monitoring, control, and management of power loads, providing technological support for their realization. With rapid economic development and continuous social progress, electricity demand continues to grow. This places higher demands on the stable operation and reliable power supply of the power system, requiring advanced systems for real-time monitoring and control of power loads.

[0003] Therefore, a technical solution is needed that has strong compatibility and scalability, updates monitoring data in real time, improves energy management, significantly enhances user experience, enables rapid fault location and recovery, optimizes resource allocation, saves costs and reduces energy consumption. Summary of the Invention

[0004] This invention aims to provide a system, method, and computing device for intelligent energy management, which has strong compatibility and scalability, updates monitoring data in real time, improves energy management level, significantly enhances user experience, enables rapid fault location and recovery, optimizes resource allocation, saves costs, and reduces energy consumption.

[0005] According to one aspect of the present invention, a system for intelligent energy management is provided, the system having a four-level architecture, the system comprising a first level, a second level, a third level, and a fourth level, wherein:

[0006] The first level configuration is as follows:

[0007] Responsible for data storage, processing, and analysis;

[0008] Provides a visual energy management interface;

[0009] The second-level configuration is as follows:

[0010] At least one data transmission method is used to transmit data between the first layer and the third layer;

[0011] The third-level configuration is as follows:

[0012] Data is transmitted with the second layer via the uplink communication interface;

[0013] Use edge computing devices to calculate and manage energy data;

[0014] Data is transmitted with the fourth layer via the downlink communication interface;

[0015] The fourth-level configuration is as follows:

[0016] Data is collected through energy monitoring terminals.

[0017] According to some embodiments, the first level is further configured as follows:

[0018] Store the data in a cloud database;

[0019] Big data analysis and machine learning are performed using data from the cloud database.

[0020] Data, function commands, and control instructions are sent to the third level.

[0021] According to some embodiments, the third level is further configured as follows:

[0022] The edge computing device collects energy data information from the terminal device via a serial port.

[0023] The energy data information is stored in the data center of the edge computing device.

[0024] According to some embodiments, the third level is further configured as follows:

[0025] The computing module in the edge computing device reads the energy data information from the data center and performs calculations.

[0026] The algorithm module in the edge computing device makes decisions based on the energy data information;

[0027] The edge computing device reports the analysis results to the first level and receives control commands issued by the first level.

[0028] According to some embodiments, the third layer is further configured such that the edge computing device provides local control and decision support for the fourth layer.

[0029] According to some embodiments, the third level is further configured as follows:

[0030] The smart energy unit uses a three-layer structure of software applications, basic support, and hardware modules to collect and control data.

[0031] According to some embodiments, the third level interacts through an interactive interface, the interactive interface including:

[0032] The always-on display interface shows the real-time energy load value of the total power supply group, the total power supply group load curve, the set values ​​of the control parameters that have been put into operation, the currently put into operation control parameters, the current number of control cycles put into operation, the current remote signaling status information, the system clock, and the status diagram of each channel.

[0033] A login interface, which provides a user login entry point;

[0034] An energy management interface, used to monitor and control energy performance and energy efficiency;

[0035] The demand-side response interface is used to display current energy usage and current demand-side response event information.

[0036] According to another aspect of the present invention, a method for intelligent energy management is provided for managing energy data, the method comprising:

[0037] Perform the following operations at the first level:

[0038] Responsible for data storage, processing, and analysis;

[0039] Provides a visual energy management interface;

[0040] Perform the following operations at the second level:

[0041] At least one data transmission method is used to transmit data between the first layer and the third layer;

[0042] Perform the following operations at the third level:

[0043] Data is transmitted with the second layer via the uplink communication interface;

[0044] The smart energy unit, composed of a three-layer structure of software applications, basic support, and hardware modules, collects and controls data.

[0045] Use edge computing devices to calculate and manage energy data;

[0046] Data is transmitted with the fourth layer via the downlink communication interface;

[0047] Perform the following operations at the fourth level:

[0048] Data is collected through energy monitoring terminals.

[0049] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method as described in any of the preceding claims.

[0050] According to another aspect of the present invention, a computing device is provided, comprising:

[0051] Processor; and

[0052] A memory that stores a computer program, which, when executed by the processor, implements the method as described in any of the preceding methods.

[0053] According to embodiments of the present invention, a four-level architecture is used to realize functions such as data acquisition, data storage, analysis and calculation, event logging, information feedback, and load regulation. The first level is responsible for data storage, processing, and analysis, providing a visual energy management interface. The second level uses at least one data transmission method to transmit data between the first and third levels. The third level transmits data with the second level through an uplink communication interface, uses an edge computing device to calculate and manage energy data, and transmits data with the fourth level through a downlink communication interface. The fourth level uses an energy monitoring terminal and is used for system data acquisition. The system of the present invention has strong compatibility and scalability, updates monitoring data in real time, improves energy management level, significantly enhances user experience, enables rapid fault location and recovery, optimizes resource allocation, saves costs, and reduces energy consumption.

[0054] According to some embodiments, the present invention achieves intuitive visualization. Traditional energy management systems often present complex data tables and technical terms, which are difficult for non-professional users to understand and operate. However, the system of the present invention uses an intuitive graphical interface to display energy data in a visual way, such as bar charts, line charts, pie charts, etc., so that users can understand the energy usage, trend changes, etc. at a glance.

[0055] According to some embodiments, the system of the present invention has strong interactivity and can provide rich interactive functions. Users can interact with the system through clicks, swipes, and other operations. Users can directly set the device's operating parameters, timer switches, etc., on the interface without needing to operate through complex command lines or professional software. At the same time, when an alarm occurs, the terminal can report audible and visual alarms to help users locate the fault.

[0056] According to some embodiments, the system of the present invention can provide personalized customization, and different users can customize different energy management solutions according to their own usage scenarios and needs to meet diverse needs.

[0057] According to some embodiments, the system of the present invention has the advantage of cross-platform compatibility, can be deployed on various terminals in a web-based manner, and can add new energy indicator monitoring and support more types of energy devices according to user needs. This flexibility enables the smart energy unit to continuously adapt to new application scenarios and requirements, maintaining its technological advancement and competitiveness.

[0058] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit the invention. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0060] Figure 1 shows a schematic diagram of a smart energy system according to an example embodiment.

[0061] Figure 2 shows a flowchart of a method for operating a smart energy system according to an example embodiment.

[0062] Figure 3 shows a flowchart of data transmission according to an example embodiment.

[0063] Figure 4 shows a schematic diagram of a smart energy system according to an example embodiment.

[0064] Figure 5 shows a schematic diagram of the interface classification of a smart energy system according to an example embodiment.

[0065] Figure 6 illustrates a schematic diagram of a fault handling process according to an example embodiment.

[0066] Figure 7 shows a block diagram of a computing device according to an exemplary embodiment. Detailed Implementation

[0067] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that the invention will be thorough and complete, and the concept of the exemplary embodiments will be fully conveyed to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0068] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a full understanding of embodiments of the invention. However, those skilled in the art will recognize that the technical solutions of the invention can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of the invention.

[0069] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0070] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0071] It should be understood that although the terms first, second, third, etc., may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another. Therefore, the first component discussed below may be referred to as the second component without departing from the teachings of the present invention. As used herein, the term "and / or" includes all combinations of any one and more of the associated listed items.

[0072] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this invention are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0073] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of exemplary embodiments, and the modules or processes in the drawings are not necessarily essential for implementing the present invention, and therefore cannot be used to limit the scope of protection of the present invention.

[0074] In recent years, the smart grid industry has received significant support from national policies, with relevant departments issuing a series of policies to promote its development and innovation. With the continuous advancement of information and digital technologies and the popularization of new energy power generation, the Chinese smart grid market is expanding rapidly. A key trend in smart grid management is digital transformation, which involves introducing advanced sensing and measurement technologies, control methods, and decision support systems to achieve the goals of grid reliability, safety, economy, efficiency, environmental friendliness, and operational safety. Smart grid management also relies on integrated, high-speed, two-way communication networks to support real-time data transmission and processing.

[0075] With the transformation of the energy structure and the large-scale integration of renewable energy, the stable operation of the power grid faces numerous uncertainties. In smart grid management, data monitoring, collection, computation, and storage are significant challenges. The data generated by the power system is growing exponentially every day, and power companies need to address issues such as large data volumes and heterogeneous data sources. Efficiently processing and storing this data is a major pain point. Smart grid management relies on advanced technologies and equipment, and the timely updating and maintenance of these technologies place high demands on the operation and management of power companies.

[0076] Therefore, this invention proposes a system and method for intelligent energy management, which has strong compatibility and scalability, updates monitoring data in real time, improves energy management and control, significantly enhances user experience, enables rapid fault location and recovery, optimizes resource allocation, saves costs and reduces energy consumption.

[0077] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention.

[0078] Figure 1 shows a schematic diagram of a smart energy system according to an example embodiment.

[0079] Referring to Figure 1, which illustrates the four-level architecture of a smart energy system for managing energy data, the system includes a first level, a second level, a third level, and a fourth level.

[0080] According to the example embodiment, the first level is configured to be responsible for data storage, processing and analysis; and to provide a visual energy management interface.

[0081] According to some embodiments, the first layer is further configured to: store data in a cloud database; perform big data analysis and machine learning using the data in the cloud database; and issue data, function commands, and control instructions to the third layer. The first layer, as a cloud platform layer, provides highly reliable and secure data storage services.

[0082] According to an example embodiment, the second layer is configured to: use at least one data transmission method to perform data transmission between the first layer and the third layer.

[0083] According to some embodiments, the second layer can employ data transmission methods such as fiber optic cables, private wireless networks, 5G channels, and wireless virtual private networks. As a pipeline transmission layer, the second layer provides a data transmission channel between the first and third layers, ensuring stable data transmission.

[0084] According to the example embodiment, the third layer is configured to: transmit data with the second layer via an uplink communication interface; use an edge computing device to calculate and manage energy data; and transmit data with the fourth layer via a downlink communication interface.

[0085] According to some embodiments, the third layer is further configured as follows: the edge computing device collects energy data information from the terminal device via a serial port; and stores the energy data information in the data center of the edge computing device. The computing module in the edge computing device reads the energy data information from the data center and performs calculations; the algorithm module in the edge computing device makes decisions based on the energy data information; the edge computing device reports the analysis results to the first layer and receives control commands issued by the first layer. The edge computing device provides local control and decision support for the fourth layer. The smart energy unit performs data collection and control through a three-layer structure of software applications, basic support, and hardware modules.

[0086] According to some embodiments, the edge computing device collects electrical data such as voltage, current, and power of the terminal device through a RS485 serial port; stores the above data in the data center of the edge computing device, where it is read and calculated by the computing module; the algorithm module makes decisions based on the collected data to achieve effective management of the energy system; and the edge computing device reports the analysis results to the cloud platform and receives control commands issued by the cloud platform.

[0087] Edge computing devices transmit data to the cloud platform. After processing and filtering by the edge computing devices, valuable data is uploaded to the cloud platform for storage and further analysis. This data provides a rich data source for big data analytics and machine learning on the cloud platform, helping users better understand business conditions and user needs. The cloud platform can also issue data and commands to the edge computing devices. For example, the cloud platform can push updated software versions to the edge computing devices to keep them up-to-date with functionality and performance. Simultaneously, the cloud platform can issue control commands to edge devices based on global business needs, enabling centralized management of the new load management system.

[0088] The smart energy unit collects data from the fourth level. Using specific communication protocols, the smart energy unit collects electrical data such as voltage, current, power, and electricity consumption processed by end devices via physical interfaces such as carrier waves, 5G, and serial ports. The fourth-level acquisition method uses built-in current and voltage transformers to measure the current and voltage in the circuit. Internal high-precision metering chips record these measurements in real time. These metering chips act as a small data processing center, converting the collected analog electrical signals into digital signals and processing and storing the data. Data collected includes voltage, current, and electricity consumption. End devices in the fourth level include electricity meters and branch monitoring units. The smart energy unit collects this data and performs preliminary processing and analysis, reducing the burden on end devices. Edge computing devices filter, compress, and aggregate data, reducing data transmission volume and storage requirements, thus lowering the energy consumption and computational pressure on end devices. The smart energy unit provides local control and decision support for end devices. Because the edge computing devices are located close to the end devices, they can quickly respond to local events, enabling real-time control and decision-making, while also collaborating with end devices to improve system performance. Edge computing devices and end devices can collaborate to achieve more efficient task execution.

[0089] According to the example embodiment, the fourth level configuration is: data collection is performed through an energy monitoring terminal.

[0090] According to some embodiments, the end devices in the fourth layer include load devices such as charging piles, distributed power sources, and distributed energy storage, which interact with the third layer through communication methods such as RS485, Ethernet, and high-speed power line carrier (HPLC) for the third layer to perform calculations and analyses.

[0091] This layered architecture gives the system high scalability and compatibility. As technology advances and needs change, new end devices can be easily added or cloud platform functionality upgraded without affecting the overall system stability. Simultaneously, communication between different layers via standardized interfaces improves system integration and interoperability.

[0092] It can be widely used in factories, residences, office buildings, and other places, and has strong compatibility and scalability. Through the touch screen, it can realize functions such as displaying electricity meter data, changing radio channels, and setting power control parameters, which can significantly improve the user experience, improve the level of power distribution load management, reduce energy consumption, quickly locate and recover from faults, and optimize the allocation of power resources.

[0093] Figure 2 shows a flowchart of a method for operating a smart energy system according to an example embodiment.

[0094] Referring to Figure 2, in S201, the fourth level collects data from user load equipment through the energy monitoring terminal.

[0095] According to some embodiments, the fourth-level energy monitoring terminal includes data acquisition instruments, sensors, controllers, load switches, etc. The fourth level acquires data from user load devices, including industrial interruptible loads, industrial adjustable loads, building HVAC loads, distributed power sources, distributed energy storage, charging piles, etc.

[0096] In S203, the third layer obtains real-time energy data from the fourth layer through the downlink communication interface.

[0097] According to some embodiments, the downlink communication interface of the third layer acquires real-time energy data from the fourth layer through wired methods including RS485, Ethernet, etc., wireless methods including WAN, Bluetooth, etc., and dual-mode transmission of high-speed power line carrier HPLC and high-frequency radio frequency HRF.

[0098] In S205, the third level performs data analysis and calculations.

[0099] The third-level algorithm module reads data from the data center, performs real-time analysis and calculations on the preprocessed data, and uses machine learning algorithms, statistical analysis, and other methods to analyze historical and real-time data to predict equipment failures and optimize power dispatch. For example, it performs power quality analysis, equipment status monitoring, and fault diagnosis.

[0100] In S207, the third level makes decisions through a data analysis and computation interface.

[0101] The third level analyzes the data to determine the possible types of faults, and then performs collaborative analysis across modules. For example, the interface display module presents abnormal data in a visual way, providing basic information about the faulty equipment so that maintenance personnel can quickly understand the fault situation; the demand-side response module analyzes the impact of the fault on power demand forecasting based on historical electricity consumption data and the current fault situation, and assesses whether the demand-side response strategy needs to be adjusted; the energy efficiency management module analyzes the energy consumption of the faulty equipment, determines the degree of impact of the fault on energy efficiency, and issues early warning notifications after the fault is analyzed, ensuring that maintenance personnel can receive alarm information in a timely manner.

[0102] In S209, the third layer transmits data to the first layer through the second layer.

[0103] The smart energy unit stores abnormal data in a data center and performs in-depth analysis using algorithm modules. By comparing historical data and analyzing data trends, the specific causes and severity of the faults are determined. Then, some key data is transmitted to a central server or cloud platform for further analysis and global decision-making, enabling distributed intelligent control through collaboration.

[0104] For example, power data of the transformer area is collected by voltage and current sensors, and then the data format is converted to improve the data quality. Based on the real-time power curve data analysis and calculation, local decisions are made, and finally the data is reported to the master station for coordinated control.

[0105] In S211, the first level performs data storage and analysis.

[0106] The first layer transmits data from the third layer through the second layer's pipeline. The second layer's transmission methods include fiber optic cables, private wireless networks, 5G channels, and wireless virtual private networks.

[0107] The cloud platform stores and further analyzes valuable data, which provides a rich data source for big data analytics and machine learning on the cloud platform, helping users better understand business conditions and user needs.

[0108] The following describes the workflow of an edge computing device, with specific steps as follows:

[0109] Step 1: Acquire electrical data such as voltage, current, and power from the end devices via an RS485 serial port. The smart energy unit plays a crucial role in the energy management system. It establishes communication connections with end devices such as charging piles and energy storage systems using power protocols. Through these protocols, the smart energy unit can efficiently acquire various key parameters from the end devices, including electricity consumption, power, voltage, and current. These parameters are essential for a comprehensive understanding of the energy system's operating status.

[0110] Step 2: The above data is stored in the data center of the edge computing device, where the computing module reads and performs calculations. The collected data from the end devices is stored in the data center as a database. This storage method ensures data security and accessibility, while also providing rich data resources for subsequent algorithm analysis. The database can be a relational or non-relational database, selected and configured according to actual needs. During data storage, data cleaning and preprocessing can also be performed to improve data quality and availability.

[0111] Step 3: The algorithm module makes decisions based on the collected data to achieve effective management of the energy system. One possible scenario is as follows:

[0112] Alarm mechanism in power control mode. When power control is enabled and effective, the terminal collects total load data every minute. If the total load reaches or exceeds the power setpoint corresponding to the power control period (this power is provided by the master station or calculated from parameters given by the master station), the terminal will issue a load over-limit alarm according to the set alarm time, prompting the user to check the overload. At this time, the user should take timely measures to reduce the load and lower the total power below the current setpoint. This alarm mechanism can promptly remind users of the load status of the energy system, prompting users to actively participate in energy management and avoid system failures or energy waste caused by excessive load.

[0113] Tripping action after load overload. If the load continuously exceeds the limit for a period equal to or exceeding the power control alarm time (the alarm time is set by the master station, with a default value of 3 minutes), the alarm ends, and the highest priority controllable switch with power control enabled and in the closed position is tripped according to the tripping sequence. This measure is to automatically disconnect part of the load when the load continues to exceed the limit, thereby protecting the safe and stable operation of the energy system. The tripping sequence can be adjusted according to the importance and priority of the load to ensure that the impact on critical loads is minimized.

[0114] Handling of persistent overloads. After a trip, if the current load remains higher than the control setpoint, the system will sequentially execute the next round of alarms and trips, and so on. This continuous monitoring and control mechanism ensures that the energy system continuously adjusts under abnormal load conditions until the load returns to a safe range. It also reminds users to take further effective load-reduction measures to avoid the adverse effects of frequent system trips on equipment and daily life.

[0115] Step 4: The edge computing device reports the analysis results to the cloud platform and receives control commands issued by the cloud platform.

[0116] The smart energy unit utilizes various power protocols to establish communication connections with end devices, ensuring efficient and accurate data acquisition. Database storage methods and data cleaning and preprocessing improve data quality and availability, providing a reliable data foundation for algorithm analysis. Algorithm modules such as alarm mechanisms for power control activation, tripping actions after load overload, and continuous overload handling enable real-time monitoring and automatic control of the energy system. These mechanisms can promptly alert users and automatically take measures to ensure the safe and stable operation of the energy system, reducing the probability and impact of faults.

[0117] Figure 3 shows a flowchart of data transmission according to an example embodiment.

[0118] See Figure 3, at 3201, the data is collected from the terminal device.

[0119] Smart energy units acquire data from end devices through wired and wireless transmission methods. Wired methods include RS485 and Ethernet, while wireless methods include WAN and Bluetooth. They can also utilize a dual-mode transmission method combining high-speed power line carrier (HPLC) and high-frequency radio frequency (HRF).

[0120] Terminal equipment collects various data in real time, including voltage, current, power, and equipment temperature, through sensors installed on power equipment, such as voltage transformers, current transformers, and temperature sensors.

[0121] In S303, data is written to the data center.

[0122] After acquiring data, the smart energy unit performs preliminary processing on the collected data, including data cleaning, noise reduction, and format conversion, to improve data quality. Then, the processed data is written to the data center, waiting for the computing module to read and perform calculations.

[0123] In S305, the algorithm module analyzes the collected data.

[0124] The algorithm module reads data from the data center and performs real-time analysis and calculations on the preprocessed data. For example, it performs power quality analysis, equipment status monitoring, and fault diagnosis. Machine learning algorithms and statistical analysis methods can be used to analyze historical and real-time data to predict equipment failures and optimize power dispatching.

[0125] In S307, determine whether a warning has been generated.

[0126] Based on the analysis results, determine whether an energy failure has occurred and generate a warning, then make a local decision and execute control operations. If a failure occurs, display an alarm on the interface, deactivate protective measures, and then feed the results back to the cloud platform. If no failure occurs, feed the results back to the cloud platform.

[0127] In S309, an alarm is displayed on the interface.

[0128] If a malfunction occurs, the smart energy unit will issue an alarm and display fault information through the interface application.

[0129] In S311, the remote device performs a protective operation.

[0130] After an alarm is displayed on the interface, the control equipment takes protective measures. For example, when a equipment failure is detected, an alarm is issued promptly and corresponding protective measures are taken; during peak electricity demand periods, the output power of distributed energy sources is adjusted.

[0131] In S313, the results are fed back to the cloud platform.

[0132] Some key data is transmitted to a central server or cloud platform for more in-depth analysis and global decision-making, enabling distributed intelligent control through collaboration.

[0133] The smart energy unit achieves effective management of terminal equipment such as charging piles and energy storage through data collection, storage, and algorithm analysis. Its decision-making and execution process can respond promptly to load changes, ensuring the safe and stable operation of the energy system and providing strong support for realizing intelligent energy management.

[0134] This invention utilizes comprehensive environmental data perception and swarm intelligence calculations at the end of the power distribution load management system to automatically optimize transformer substation power. While meeting basic user electricity needs, it performs partial switch tripping, thereby reducing energy consumption and promoting low-carbon operation. Secondly, it grants on-site maintenance personnel certain permissions. On the one hand, they can visually view data from end-devices on the power distribution load control terminal, identify branches with high power consumption, and take appropriate action. On the other hand, they can adjust power parameters according to the actual needs of the substations via touchscreen settings, improving the reliability, security, and efficiency of the power grid.

[0135] Figure 4 shows a schematic diagram of a smart energy system according to an example embodiment.

[0136] The UI-based smart energy unit adopts a layered architecture design, including four layers: cloud, network, edge, and terminal. The first layer, the cloud platform, is responsible for data storage, processing, and analysis, providing users with a visual energy management interface. The second layer, the management channel, uses various methods such as fiber optic, wireless private network, 5G channel, and wireless virtual private network to ensure stable data transmission. The third layer, the edge device, specifically refers to the smart energy unit in this invention, which realizes energy data acquisition and control. The fourth layer, the terminal device, includes load devices such as charging piles, distributed power sources, and distributed energy storage, which interact with the smart energy unit through communication methods such as RS485, Ethernet, and HPLC for calculation and analysis.

[0137] The smart energy unit plays a crucial role in the entire energy management system, encompassing several key aspects, including extremely important applications such as interface display, demand-side response, orderly charging, and energy efficiency management.

[0138] The interface display application interacts with the main control board of the smart energy unit through Message Queue Telemetry Transmission (MQTT) to display data information, alarm status, parameter information, etc. of devices such as charging piles and electricity meters. The screen turns off after 5 minutes of inactivity on site, so that on-site maintenance personnel can obtain the energy information of the transformer area in a timely manner.

[0139] The aforementioned demand-side response application uses historical electricity consumption data and economic indicators to predict future electricity demand. Accurate demand forecasting helps power system operators prepare in advance and optimize power supply. Simultaneously, the implementation effectiveness of demand-side response projects is evaluated, including load shedding, user participation, and power system stability. Through evaluation, demand-side response strategies and measures are continuously improved.

[0140] The aforementioned orderly charging application can monitor the power grid load in real time and intelligently adjust the charging plan according to the power supply and demand situation at different times. It automatically starts charging during off-peak hours to avoid excessive pressure on the power grid during peak hours, thus achieving a rational allocation of power resources.

[0141] The energy efficiency management application has the capability to monitor multiple energy types simultaneously, meeting the comprehensive energy management needs of different users. Whether it's the electricity from industrial enterprises or commercial buildings, the energy efficiency management module can perform comprehensive monitoring. Simultaneously, it conducts in-depth analysis of the collected energy data to understand energy usage trends, peak and off-peak periods, and the energy consumption ratio of different equipment. Through data analysis, it identifies energy waste and potential energy-saving opportunities.

[0142] Figure 5 shows a schematic diagram of the interface classification of a smart energy system according to an example embodiment.

[0143] This invention is an edge computing device deployed on the customer side under the "cloud-pipe-edge-device" architecture of a new type of power load management system. It is a device that communicates bidirectionally with user power loads and distributed energy systems to realize functions such as data acquisition, data storage, analysis and calculation, event recording, information feedback, and load regulation, and can meet the edge business needs of the new load management system.

[0144] Traditionally, maintenance personnel rely on button operations to modify internal parameters of smart energy units and view data collected by end devices. This method has several drawbacks. First, the operation process is cumbersome and complex, consuming a significant amount of time and energy for maintenance personnel. Second, the display interface is a monotonous black-and-white screen with poor visual effects, making it difficult for maintenance personnel to quickly and accurately obtain information and extremely inconvenient for troubleshooting. The black-and-white screen display lacks intuitiveness and appeal, making it difficult for maintenance personnel to quickly distinguish key information when faced with large amounts of data and complex situations, thus increasing the difficulty of the work and the risk of errors.

[0145] To address this, the present invention utilizes a UI-based smart energy unit that embeds advanced display devices, employing a color touchscreen to vividly and aesthetically display load data in a graphical format. This display method not only provides a visually pleasing experience, but more importantly, the charts intuitively present data trends and relationships, enabling maintenance personnel to easily understand and analyze the data. For more detailed data, a tabular interface is also available, offering greater clarity and intuitiveness. The tabular format accurately displays the specific values ​​of each data point, facilitating precise data analysis and comparison by maintenance personnel, thereby enabling more efficient problem diagnosis and decision-making.

[0146] The main user interface (UI) components of the smart energy unit are shown in Figure 5, including a constantly displayed interface, a login interface, and a main interface. The constantly displayed interface includes a load management interface, and the main interface includes an air conditioning management interface, a demand-side response interface, and an orderly charging interface. The main interface is laid out on the display screen in a nine-grid layout. When on the constantly displayed interface or the login page, swiping left or right will exit to the nine-grid display interface, where other applications can be accessed.

[0147] The always-on interface is the load management page. This page automatically appears after the smart energy unit is powered on. The current page displays the real-time load value of the main load group 1, the load curve of the current main load group, the setpoints of the control parameters already in place, the currently applied control parameters, the status of the currently applied control cycle, the current remote signaling status information, and the top-level display of the current system clock and the status diagrams of each channel.

[0148] The login interface requires a superuser account and password for technical personnel to access important interfaces, while other maintenance personnel can access general pages such as the always-on interface and the 5G module query interface with only ordinary permissions.

[0149] The energy management interface is an intelligent interface for monitoring and controlling energy. Firstly, it can display the real-time operating status of energy equipment, including its on / off status and operating mode. Secondly, users can operate the energy equipment through interactive buttons. Thirdly, the management interface can collect and analyze operational data from the energy system, such as temperature change curves and energy consumption. Through data analysis, users can understand the performance of energy equipment and its energy efficiency, providing a basis for optimizing equipment usage.

[0150] The demand-side response interface displays current energy usage, including parameters such as electricity consumption, power, voltage, and current, providing users with accurate decision-making support. It can also display current demand-side response event information, including event name, time, and target power reduction amount, to reduce energy consumption and improve energy efficiency.

[0151] The smart energy unit has two types of accounts: one for maintenance personnel and one for super users. Account permissions are configured during development, and users can only change the password. On-site maintenance personnel can use regular accounts to view data, parameters, and configure Ethernet and energy meter parameters. Super users, in addition to maintenance personnel permissions, can also perform operations such as setting power control parameters and changing passwords. This account classification improves account security, optimizes management efficiency, and enhances the user experience.

[0152] The smart energy unit can display primary and secondary data from energy devices on its interface. Primary data comes directly from electrical quantities from primary equipment in the power system. Primary equipment mainly refers to devices that directly participate in the production, transmission, distribution, and consumption of electrical energy, such as generators, transformers, circuit breakers, and transmission lines. Secondary data consists of low-voltage and low-current signals transformed by instrument transformers, as well as various electrical parameters, status information, and control commands obtained after processing by measuring instruments and automation systems.

[0153] The displayed content is updated in real time based on changes in telemetry values ​​of corresponding devices in the data center. Clicking on a data item on the screen retrieves historical data for that data item and displays it as a curve. This function is primarily implemented through MQTT messages, with topics including device information query, real-time data query, and historical data query.

[0154] For example, the message bodies for device information query ({app} / get / request / database / register), real-time data query ({app} / get / request / database / realtime), and historical data query ({app} / get / request / database / history) are shown in Tables 1, 2, and 3.

[0155] Table 1 Equipment Information Query Interface

[0156] Table 1 shows the device information query interface, which includes the device's model name, port, unique device identifier, physical address, description, and other information.

[0157] Table 2 Real-time Data Query Interface

[0158] Table 2 shows the real-time data query interface, which includes the name of the data to be queried, the unique identifier of the device, and the current data of the device returned by the data center.

[0159] Table 3 Historical Data Query Interface

[0160] Table 3 shows the historical data query interface, which includes the name of the data to be queried, the start time, the end time, and the device's unique identifier. The data center returns all stored data within the query period.

[0161] When the smart energy unit's algorithm module calculates and detects that the power exceeds the threshold for a certain period of time, a pop-up window displays a trip alarm message, and the system pushes the event content in Mandarin voice broadcast. The alarm stops after the alarm time expires, and the screen turns off and disappears after 5 minutes of inactivity. Simultaneously, the interface can automatically adjust the volume and interact with the main control board via broadcast messages. It issues audible alarms when important events such as tripping, parameter changes, or power outages occur, prompting maintenance personnel to promptly detect faults and tripping information. The power threshold and time can be set through the system; if the user does not set them, there are no fixed thresholds or times, and no related decisions or controls will be implemented.

[0162] The smart energy unit supports reading and setting radio parameters, and displays and modifies radio frequencies and channel numbers. There are 48 channels, each corresponding to a different frequency range of 223.025-235MHz. Frequency selection is possible within this range for all 48 channels. Radio communication is bidirectional, and its construction and maintenance costs are relatively low. Compared to mobile communication systems that require extensive base station construction and complex network maintenance, radio communication equipment is typically simpler, cheaper, and requires less infrastructure investment. Radios are highly independent and do not rely on external networks. Unlike internet or mobile communication, radio communication does not depend on central servers or network operator infrastructure, exhibiting high independence and autonomy. This allows radio communication to continue operating normally in special circumstances, such as network attacks, war, or network outages, providing reliable communication for users. Radio communication technology saves a significant amount of wiring work and effectively solves the real-time problem of massive terminal access.

[0163] By aggregating and calculating the voltage, current, and other data transmitted from the terminal acquisition equipment, the load curve of the distribution area is obtained. The demand-side response interface can analyze the electricity consumption behavior characteristics of users based on these curves, helping users to better participate in demand-side response, achieve efficient use and conservation of energy, and contribute to the stable operation of the power system.

[0164] The smart energy unit can be connected to the charging piles in the distribution area via network cable. The distribution area manager can understand the charging status and progress in real time through the orderly charging management interface, and issue orderly charging decisions based on the analysis of the aggregation computing module, thereby realizing the optimized use of energy, reducing charging costs, and improving grid stability.

[0165] This invention employs edge computing technology to offload some data processing and analysis functions to the smart energy unit, reducing data transmission volume and the burden on the main station system. The smart energy unit can perform preliminary analysis of the collected data locally, filtering out key information for display. This allows the data collected by the smart energy unit to be presented more intuitively to the user, improving the user experience. Simultaneously, it adds a screen-off function for prolonged periods of inactivity, reducing device energy consumption, avoiding resource waste, and improving system response speed and efficiency.

[0166] Figure 6 illustrates a schematic diagram of a fault handling process according to an example embodiment.

[0167] When a fault occurs in the end device, such as hardware damage, software failure, or communication interruption, the end device sends an abnormal signal to the smart energy unit via communication methods such as RS485, Ethernet, or HPLC. When data anomaly is detected, the smart energy unit's edge devices continuously collect data from the end device. By monitoring key parameters such as electricity consumption, power, voltage, and current in real time, data anomalies are detected. For example, when power suddenly fluctuates significantly or voltage exceeds the normal range, the fault detection mechanism is triggered.

[0168] The smart energy unit performs preliminary analysis on the collected abnormal data to determine the possible types of faults. For example, if multiple end devices experience communication interruptions simultaneously, it may indicate a problem with the management channel; if the power of a charging pile increases abnormally, it may indicate an internal fault in the charging pile.

[0169] Following initial analysis, a collaborative module analysis is conducted. The interface display module presents abnormal data in a visual manner, such as displaying a red alarm icon on a color touchscreen, while also providing basic information about the faulty equipment, allowing maintenance personnel to quickly understand the fault situation. The demand-side response module analyzes the impact of the fault on electricity demand forecasting based on historical electricity consumption data and the current fault situation, assessing whether adjustments to the demand-side response strategy are necessary. The orderly charging module checks whether the fault affects the charging plan of energy equipment; if necessary, it adjusts the charging strategy to avoid further impact on the grid load. The energy efficiency management module analyzes the energy consumption of the faulty equipment to determine the degree of impact of the fault on energy efficiency. The smart energy unit stores abnormal data in a database and uses the algorithm module for in-depth analysis. By comparing historical data and analyzing data trends, the specific cause and severity of the fault are determined.

[0170] Upon detecting a fault, an early warning notification is issued. Based on the fault analysis results, the smart energy unit generates corresponding alarm information, including the name of the faulty device, fault type, severity, and potential impact range. The appropriate notification module is selected based on the alarm level and preset notification rules. For example, for severe faults, the notification interface simultaneously displays the alarm information through applications, SMS platforms, and email systems, ensuring that maintenance personnel receive the alarm information promptly. The interface display module pops up an alarm window on a color touchscreen, displaying detailed alarm information and emitting sound or flashing alerts to attract the attention of on-site maintenance personnel.

[0171] Upon receiving alarm information, maintenance personnel take appropriate measures based on the type and severity of the fault. For cases that may be hardware failures, maintenance personnel will visit the faulty equipment on-site to inspect and confirm the specific nature of the fault. For faults that can be diagnosed remotely, maintenance personnel will utilize the remote control function of the smart energy unit to perform parameter adjustments, software upgrades, and other operations to attempt to restore normal equipment operation. For faults involving multiple departments or requiring external resource support, maintenance personnel will promptly coordinate with relevant personnel and units to jointly resolve the fault.

[0172] After troubleshooting, maintenance personnel re-inspect and test the faulty equipment to confirm it has returned to normal operation. The smart energy unit continuously monitors data from the end devices to verify whether the fault has been completely eliminated. If the data returns to normal, the system automatically clears the alarm. The fault handling process is recorded and summarized, including the cause of the fault, the handling measures, and the handling time. These records can provide a reference for future fault handling and also help to continuously improve the stability and reliability of the system.

[0173] Figure 7 shows a block diagram of a computing device according to an exemplary embodiment.

[0174] As shown in Figure 7, the computing device 30 includes a processor 12 and a memory 14. The computing device 30 may also include a bus 22, a network interface 16, and an I / O interface 18. The processor 12, memory 14, network interface 16, and I / O interface 18 can communicate with each other via the bus 22.

[0175] Processor 12 may include one or more general-purpose CPUs (Central Processing Units), microprocessors, or application-specific integrated circuits, for executing relevant program instructions. According to some embodiments, computing device 30 may also include a high-performance display adapter (GPU) 20 for accelerating processor 12.

[0176] Memory 14 may include a machine-readable medium in the form of volatile memory, such as random access memory (RAM), read-only memory (ROM), and / or cache memory. Memory 14 is used to store one or more programs containing instructions, as well as data. Processor 12 may read the instructions stored in memory 14 to perform the methods described above according to embodiments of the present invention.

[0177] The computing device 30 can also communicate with one or more networks via the network interface 16. The network interface 16 can be a wireless network interface.

[0178] Bus 22 can include address bus, data bus, control bus, etc. Bus 22 provides a path for exchanging information between components.

[0179] It should be noted that, in specific implementations, the computing device 30 may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the device described above may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0180] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), network storage devices, cloud storage devices, or any type of medium or device suitable for storing instructions and / or data.

[0181] This invention also provides a computer program product comprising a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0182] Those skilled in the art will clearly understand that the technical solutions of the present invention can be implemented by means of software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware capable of independently performing or cooperating with other components to perform a specific function, wherein the hardware may be, for example, a field-programmable gate array (FPGA), an integrated circuit, etc.

[0183] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0184] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0185] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0186] The units described as separate components may or may not be physically separate. 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0187] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0188] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention.

[0189] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0190] Exemplary embodiments of the present invention have been specifically shown and described above. It should be understood that the present invention is not limited to the detailed structures, arrangements, or implementations described herein; rather, the present invention is intended to cover various modifications and equivalent arrangements contained within the spirit and scope of the appended provisions.

Claims

1. A system for intelligent management of energy, the system is a four-level architecture, characterized in that, The system comprises a first level, a second level, a third level, and a fourth level, wherein: The first level configuration is as follows: Responsible for data storage, processing, and analysis; Provides a visual energy management interface; The second-level configuration is as follows: At least one data transmission method is used to transmit data between the first layer and the third layer; The third-level configuration is as follows: Data is transmitted with the second layer via the uplink communication interface; Use edge computing devices to calculate and manage energy data; Data is transmitted with the fourth layer via the downlink communication interface; The fourth-level configuration is as follows: Data is collected through energy monitoring terminals.

2. The system of claim 1, wherein, The first level is also configured as follows: Store the data in a cloud database; Big data analysis and machine learning are performed using data from the cloud database. Data, function commands, and control instructions are sent to the third level.

3. The system of claim 1, wherein, The third level is also configured as follows: The edge computing device collects energy data information from the terminal device via a serial port. The energy data information is stored in the data center of the edge computing device.

4. The system of claim 1, wherein, The third level is also configured as follows: The computing module in the edge computing device reads the energy data information from the data center and performs calculations. The algorithm module in the edge computing device makes decisions based on the energy data information; The edge computing device reports the analysis results to the first level and receives control commands issued by the first level.

5. The system of claim 1, wherein, The third layer is further configured such that the edge computing device provides local control and decision support for the fourth layer.

6. The system of claim 1, wherein, The third level is also configured as follows: The smart energy unit uses a three-layer structure of software applications, basic support, and hardware modules to collect and control data.

7. The system of claim 1, wherein, The third level interacts through an interactive interface, which includes: The always-on display interface shows the real-time energy load value of the total power supply group, the total power supply group load curve, the set values ​​of the control parameters that have been put into operation, the currently put into operation control parameters, the current number of control cycles put into operation, the current remote signaling status information, the system clock, and the status diagram of each channel. A login interface, which provides a user login entry point; An energy management interface, used to monitor and control energy performance and energy efficiency; The demand-side response interface is used to display current energy usage and current demand-side response event information.

8. A method for intelligent energy management, used for managing energy data, the method comprising: Perform the following operations at the first level: Responsible for data storage, processing, and analysis; Provides a visual energy management interface; Perform the following operations at the second level: At least one data transmission method is used to transmit data between the first layer and the third layer; Perform the following operations at the third level: Data is transmitted with the second layer via the uplink communication interface; The smart energy unit, composed of a three-layer structure of software applications, basic support, and hardware modules, collects and controls data. Use edge computing devices to calculate and manage energy data; transmit data with the fourth layer through a downlink communication interface; perform the following operations through the fourth layer: collect data through the energy monitoring terminal.

9. A computer program product, characterised in that, A computer program is included, which, when executed by a processor, implements the method of claim 8.

10. A computing device, comprising: comprises: a processor; and a memory storing a computer program, which, when executed by the processor, implements the method of claim 8.

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