Smart energy management method and system based on big data of Internet of Things

Abstract

The invention relates to the technical field of energy management, in particular to a smart energy management method and system based on Internet of Things big data. The method comprises the following steps: acquiring power supply application information and power utilization data information of power utilization equipment, and performing power utilization area differentiation on the power utilization equipment based on the power supply application information and equipment position information to obtain power utilization area information of the power utilization equipment, and generating a local power grid model corresponding to the power utilization equipment according to the power utilization area information and the electric energy transmission information, and performing regional power utilization simulation detection on the power utilization state data according to the local power grid model to obtain an optimal power supply line in the power utilization area information. According to the invention, stability and high efficiency of power supply are ensured, energy waste is greatly reduced, and optimal configuration of power supply resources is realized.

Description

Technical Field

[0001] The present application relates to the technical field of energy management, and in particular to a smart energy management method and system based on Internet of Things big data. Background Art

[0002] With the application of cloud computing, big data, Internet of Things and other technologies in buildings, the deployment mode of building power infrastructure has changed, and new changes are also needed for building construction. In the construction of new buildings, the power distribution network is a crucial link.

[0003] Electricity is the basic energy source for all facilities. Like other production processes within the facility, the operation of the distribution network also needs to be monitored and managed. Distribution management is to connect intelligent power and energy devices with communication functions to software systems for data collection, status visualization, analysis and reporting functions, so as to achieve continuous monitoring and comprehensive management of the distribution system.

[0004] In current buildings, since the electrical equipment and power demand corresponding to each floor are different, the ultimate goal when designing power supply facilities and power supply lines is always to meet the power demand of the electrical equipment on each floor to ensure the normal operation of the electrical facilities on each floor. However, because of this, the power supply line corresponding to each electrical equipment on each floor has become the only power supply line used by the electrical equipment, but it is not the most energy-efficient power supply line. Therefore, how to optimize the building power supply system to meet the needs of electrical equipment on each floor and improve the overall power efficiency has become an urgent problem to be solved. Summary of the invention

[0005] In order to solve at least one of the above technical problems, the present application provides a smart energy management method and system based on Internet of Things big data.

[0006] In the first aspect, the present application provides a smart energy management method based on IoT big data, which adopts the following technical solutions: A smart energy management method based on Internet of Things big data, comprising: Acquire power application information and power consumption data information of power-consuming equipment, wherein the power application information is power supply information of power supply equipment at different locations in a building during a historical period and power transmission information of different power supply lines connected to the power supply equipment, the power-consuming equipment is the power-consuming equipment connected to the corresponding power supply line in the building during the historical period, and the power consumption data information is used to indicate the equipment location information of the power-consuming equipment and the power consumption status data of the power-consuming equipment during the historical period; Based on the power application information and the device location information, the power consumption area of ​​the power consumption device is differentiated to obtain the power consumption area information of the power consumption device; Generate a local power grid model corresponding to the power-consuming device according to the power-consuming area information and the power transmission information; The power consumption status data is subjected to regional power consumption simulation detection according to the local power grid model to obtain the best power supply line in the power consumption area information.

[0007] By adopting the above technical solutions, the power application information in the building and the detailed power consumption data of the power equipment can be fully captured and integrated. This information not only covers the historical supply capacity of the power supply equipment and the transmission status of each power supply line, but also accurately records the specific location and dynamic power consumption status of the power equipment. This all-round data collection lays a solid foundation for subsequent power consumption analysis and optimization. Based on the above rich data sources, the regional segmentation of power equipment is further realized. By intelligently analyzing the relationship between power application information and equipment location information, the system can accurately classify power equipment into the power consumption area to which it belongs. This step effectively improves the precision and pertinence of power consumption management. Subsequently, the system uses the power consumption area information and power transmission information to construct a highly realistic local power grid model. This model not only reflects the physical connection structure of the power grid, but also incorporates the actual distribution of power equipment and its power consumption characteristics, providing an intuitive reference for subsequent power supply optimization. Finally, based on this accurate local power grid model, it is possible to simulate and detect the power consumption status of each power consumption area under different power supply lines, and accurately identify the best power supply line through scientific calculation and comparison. This not only ensures the stability and efficiency of power supply, but also greatly reduces energy waste and achieves optimal allocation of power supply resources.

[0008] In a preferred example, the present application may be further configured as follows: the power consumption area differentiation of the power consumption equipment based on the power application information and the equipment location information to obtain the power consumption area information of the power consumption equipment includes: Determine the power supply area location and power supply coverage of different power supply devices based on the power application information; Determine a first vector set of different power supply devices and power-consuming devices based on the power supply area location and the location in the device location information; Determine whether the electric device is located in the power supply coverage range according to the first vector set. If the electric device is located in the power supply coverage range, summarize the power supply coverage range and the power supply equipment corresponding to the power supply coverage range to obtain the power consumption area information of the electric device.

[0009] In a preferred example, the present application may be further configured as follows: generating a local power grid model corresponding to the power-consuming device according to the power-consuming area information and the power transmission information includes: Determine, according to the power transmission information, line length information and environment information of the power supply line connected to the power supply device; Determine the group power node information of the power supply line according to the line length information and the environment information; Determine a second vector set of the power supply line and the power-consuming device based on the node position in the group power node information and the position in the device position information; According to the second vector set, the power transmission association between the power-consuming device and different node positions in the group power node information is constructed to obtain a power supply line grid of the power-consuming device; Constructing an initialization local area model according to the power supply coverage in the power consumption area information, and marking the power supply area location in the power consumption area information and the location in the device location information in the initialization local area model according to a preset ratio to obtain a marked local area model; The power supply line grid is integrated into the marked local model according to the corresponding relationship of the same power-consuming equipment, and the initial position node of each power supply line in the power supply line grid is connected to the power supply equipment corresponding to the power supply line to obtain a local power grid model corresponding to the power-consuming equipment.

[0010] In a preferred example, the present application may be further configured as follows: determining the group power node information of the power supply line according to the line length information and the environment information includes: Determine whether the line length information satisfies a preset line length. If so, determine the environmental parameters of nodes at different positions of the power supply line based on the environmental information, and match the environmental parameters with a preset environmental coefficient standard to obtain an initial environmental coefficient of an initial position node of the power supply line and a non-initial environmental coefficient corresponding to a non-initial position node; Calculating the environmental coefficient difference between the initial environmental coefficient and each of the non-initial environmental coefficients respectively, and determining the first non-initial position node that meets the preset environmental coefficient difference requirement in the environmental coefficient difference, defining the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and defining the position node between the new initial position node and the final position node in the non-initial environmental coefficient as a new non-initial position node; Loop execution step: calculating the environmental coefficient difference between the new initial environmental coefficient and each of the new non-initial environmental coefficients, and determining the first non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement, defining the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and defining the position node between the new initial position node and the final position node in the non-initial position node as a new non-initial position node, until there is no non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement; The group power node information of the power supply line is determined according to the initial position node and the new initial position node, and the group power node information is the power transfer switch installed at the initial position node and the new initial position node and the power transfer line connected to the power transfer switch.

[0011] In a preferred example, the present application may be further configured as follows: performing regional power consumption simulation detection on the power consumption status data according to the local power grid model to obtain the best power supply line in the power consumption area information, and then further comprising: Acquire actual power consumption information of the optimal power supply route, and calculate power loss data of power nodes in the optimal power supply route based on the actual power consumption information; Matching the calculated power loss value with the preset power loss standard to determine whether the actual power consumption information meets the preset power loss standard; If the actual power consumption information does not meet the preset power loss standard, a power supply simulation analysis is performed on the local power grid model to obtain a power grid layout instruction, and control and adjust the line layout of the power supply line connected to the power-consuming equipment.

[0012] In a preferred example, the present application may be further configured as follows: performing power supply simulation analysis on the local power grid model to obtain a power grid layout instruction includes: Determine a plurality of power supply line combinations between the power supply device and the power-consuming device according to the local power grid model; Determine the change in power consumption data corresponding to the group power node information of each power supply line combination in the plurality of power supply line combinations under the conditions of different equipment operating powers; Accumulate and calculate the power consumption data changes according to the same power supply line combination to obtain the power consumption data corresponding to each power supply line combination; Determine the line scheduling length corresponding to each power supply line combination according to the group power node information of each power supply line combination; Calculate the ratio of the power consumption data and the line scheduling length to obtain the average energy consumption data of the power supply line combination; The target power supply line combination corresponding to the minimum average energy consumption data is determined, and the power transfer switch control sequence analysis is performed on the group power node information in the target power supply line combination to obtain a power grid layout instruction.

[0013] In a preferred example, the present application may be further configured as follows: if the actual power consumption information does not meet the preset power loss standard, the following further includes: Determine the power loss data of the power supply line section corresponding to each power node information in the optimal power supply line according to the power loss data of the power node in the optimal power supply line; Calculating the ratio of the power loss data of the power supply line section to the line section length of the power supply line section to obtain the power loss value of each power supply line section; It is determined whether the power loss value of each power supply line segment meets the preset power loss standard. If not, the line corresponding to the power supply line segment in the local power grid model is marked to obtain a marked local power grid model.

[0014] In the second aspect, the present application provides a smart energy management system based on IoT big data, which adopts the following technical solutions: A smart energy management system based on Internet of Things big data, including: An information acquisition module, used to acquire power application information and power consumption data information of power-consuming devices, wherein the power application information is power supply information of power supply devices at different locations in a building during a historical period and power transmission information of different power supply lines connected to the power supply devices, the power-consuming devices are power-consuming devices connected to corresponding power supply lines in the building during the historical period, and the power consumption data information is used to indicate device location information of the power-consuming devices and power consumption status data of the power-consuming devices during the historical period; A regional differentiation module, used to differentiate the power consumption area of ​​the power-consuming device based on the power application information and the device location information, and obtain the power consumption area information of the power-consuming device; A model generation module, used to generate a local power grid model corresponding to the power-consuming device according to the power consumption area information and the power transmission information; The simulation detection module is used to perform regional power consumption simulation detection on the power consumption status data according to the local power grid model to obtain the best power supply line in the power consumption area information.

[0015] In a possible implementation, when the regional differentiation module differentiates the power consumption area of ​​the power consumption device based on the power application information and the device location information to obtain the power consumption area information of the power consumption device, it is specifically used to: Determine the power supply area location and power supply coverage of different power supply devices based on the power application information; Determine a first vector set of different power supply devices and power-consuming devices based on the power supply area location and the location in the device location information; Determine whether the electric device is located in the power supply coverage range according to the first vector set. If the electric device is located in the power supply coverage range, summarize the power supply coverage range and the power supply equipment corresponding to the power supply coverage range to obtain the power consumption area information of the electric device.

[0016] In another possible implementation, when the model generation module generates the local power grid model corresponding to the power-consuming device according to the power consumption area information and the power transmission information, it is specifically used to: Determine, according to the power transmission information, line length information and environment information of the power supply line connected to the power supply device; Determine the group power node information of the power supply line according to the line length information and the environment information; Determine a second vector set of the power supply line and the power-consuming device based on the node position in the group power node information and the position in the device position information; According to the second vector set, the power transmission association between the power-consuming device and different node positions in the group power node information is constructed to obtain a power supply line grid of the power-consuming device; Constructing an initialization local area model according to the power supply coverage in the power consumption area information, and marking the power supply area location in the power consumption area information and the location in the device location information in the initialization local area model according to a preset ratio to obtain a marked local area model; The power supply line grid is integrated into the marked local model according to the corresponding relationship of the same power-consuming equipment, and the initial position node of each power supply line in the power supply line grid is connected to the power supply equipment corresponding to the power supply line to obtain a local power grid model corresponding to the power-consuming equipment.

[0017] In another possible implementation, when the model generation module determines the group power node information of the power supply line according to the line length information and the environment information, it is specifically used to: Determine whether the line length information satisfies a preset line length. If so, determine the environmental parameters of nodes at different positions of the power supply line based on the environmental information, and match the environmental parameters with a preset environmental coefficient standard to obtain an initial environmental coefficient of an initial position node of the power supply line and a non-initial environmental coefficient corresponding to a non-initial position node; Calculating the environmental coefficient difference between the initial environmental coefficient and each of the non-initial environmental coefficients respectively, and determining the first non-initial position node that meets the preset environmental coefficient difference requirement in the environmental coefficient difference, defining the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and defining the position node between the new initial position node and the final position node in the non-initial environmental coefficient as a new non-initial position node; Loop execution step: calculating the environmental coefficient difference between the new initial environmental coefficient and each of the new non-initial environmental coefficients, and determining the first non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement, defining the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and defining the position node between the new initial position node and the final position node in the non-initial position node as a new non-initial position node, until there is no non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement; The group power node information of the power supply line is determined according to the initial position node and the new initial position node, and the group power node information is the power transfer switch installed at the initial position node and the new initial position node and the power transfer line connected to the power transfer switch.

[0018] In another possible implementation, the system further includes: a power consumption information module, an energy consumption matching module and a power supply simulation module, wherein: The power consumption information module is used to obtain actual power consumption information of the optimal power supply route, and calculate the power loss data of the group power nodes in the optimal power supply line based on the actual power consumption information; The energy consumption matching module is used to match the calculated power loss value with the preset power loss standard to determine whether the actual power consumption information meets the preset power loss standard; The power supply simulation module is used to perform power supply simulation analysis on the local power grid model when the actual power consumption information does not meet the preset power loss standard, obtain power grid layout instructions, and control and adjust the line layout of the power supply line connected to the power-consuming equipment.

[0019] In another possible implementation, when the power supply simulation module performs power supply simulation analysis on the local power grid model to obtain the power grid layout instruction, it is specifically used to: Determine a plurality of power supply line combinations between the power supply device and the power-consuming device according to the local power grid model; Determine the change in power consumption data corresponding to the group power node information of each power supply line combination in the plurality of power supply line combinations under the conditions of different equipment operating powers; Accumulate and calculate the power consumption data changes according to the same power supply line combination to obtain the power consumption data corresponding to each power supply line combination; Determine the line scheduling length corresponding to each power supply line combination according to the group power node information of each power supply line combination; Calculate the ratio of the power consumption data and the line scheduling length to obtain the average energy consumption data of the power supply line combination; The target power supply line combination corresponding to the minimum average energy consumption data is determined, and the power transfer switch control sequence analysis is performed on the group power node information in the target power supply line combination to obtain a power grid layout instruction.

[0020] In another possible implementation, the system further includes: a loss determination module, a ratio calculation module, and a line marking module, wherein: The loss determination module is used to determine the power loss data of the power supply line section corresponding to each group of power node information in the optimal power supply line according to the power loss data of the group of power nodes in the optimal power supply line; The ratio calculation module is used to calculate the ratio of the power loss data of the power supply line segment to the line segment length of the power supply line segment to obtain the power loss value of each power supply line segment; The line marking module is used to determine whether the power loss value of each power supply line segment meets the preset power loss standard. If not, the line corresponding to the power supply line segment in the local power grid model is marked to obtain the marked local power grid model.

[0021] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: at least one processor; Memory; At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned smart energy management method based on Internet of Things big data.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program, which, when executed in a computer, enables the computer to execute the above-mentioned smart energy management method based on Internet of Things big data.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: When selecting the power supply line for each power-consuming device, the power application information in the building and the detailed power consumption data of the power-consuming devices are fully captured and integrated. This information not only covers the historical supply capacity of the power supply equipment and the transmission status of each power supply line, but also accurately records the specific location and dynamic power consumption status of the power-consuming devices. This all-round data collection lays a solid foundation for subsequent power consumption analysis and optimization. Based on the above rich data sources, the regional segmentation of power-consuming devices is further realized. By intelligently analyzing the association between power application information and device location information, the system can accurately classify power-consuming devices into their power consumption areas, which effectively improves the precision and pertinence of power consumption management. Subsequently, the system uses the power consumption area information and power transmission information to construct a highly realistic local power grid model. This model not only reflects the physical connection structure of the power grid, but also incorporates the actual distribution of power-consuming devices and their power consumption characteristics, providing an intuitive reference for subsequent power supply optimization. Finally, based on this precise local power grid model, it is possible to simulate and detect the power consumption status of each power consumption area under different power supply lines, and accurately identify the best power supply line through scientific calculation and comparison. This not only ensures the stability and efficiency of power supply, but also greatly reduces energy waste and achieves optimal allocation of power supply resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of a smart energy management method based on IoT big data provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a smart energy management system based on IoT big data provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The following is combined with Figure 1 To Attachment Figure 3 This application is described in further detail.

[0026] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, those skilled in the art may make modifications to the present embodiment without any creative contribution as needed. However, as long as it is within the scope of the claims of the present application, it shall be protected by the patent law.

[0027] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0029] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0030] The embodiment of the present application provides a smart energy management method based on IoT big data, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to this. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and the embodiment of the present application does not limit this. Figure 1 As shown, the method includes: Step S10: Acquire power application information and power consumption data information of power-consuming devices.

[0031] Among them, the power application information is the power supply information of the power supply equipment in different areas of the building during the historical period and the power transmission information of different power supply lines connected to the power supply equipment. The power-consuming equipment is the power-consuming equipment connected to the corresponding power supply line in the building during the historical period. The power consumption data information is used to indicate the equipment location information of the power-consuming equipment and the power consumption status data of the power-consuming equipment during the historical period.

[0032] Specifically, the power application information indicates the power supply of power supply equipment (such as transformers, generators, etc.) deployed in different areas and floor locations within the building during the historical period. This includes key information such as the operating status, power supply, and power supply stability of the power supply equipment. At the same time, the power application information also covers the power transmission of different power supply lines connected to these power supply equipment, such as transmission efficiency, loss rate, line load, line length, and environmental parameters of the lines. Power-consuming equipment refers to various power-consuming equipment connected to specific power supply lines in the building during the historical period, such as lighting fixtures, air-conditioning equipment, office computers, etc. These devices obtain power from the power supply equipment through the power supply line to maintain their normal operation. The power consumption data information indicates the specific equipment location information (such as floor, room number, etc.) of these power-consuming equipment and their power consumption status data during the historical period. The power consumption status data includes power consumption, power consumption time, power consumption power, power consumption mode (such as standby, working, sleep, etc.), etc. These data are of great significance for analyzing building energy consumption and optimizing energy distribution.

[0033] For the embodiments of the present application, the Internet of Things (IoT) technology can be used to realize remote data collection and transmission. By installing IoT sensors and communication modules on power supply equipment, power supply lines and power consumption equipment, real-time data can be transmitted to a remote data center or cloud platform through a wireless network. Electronic devices can remotely access these data and perform online analysis and processing. Special energy consumption monitoring equipment (such as data recorders, sensors, etc.) can also be deployed to collect data. These devices can be installed at key locations of power supply equipment, power supply lines and power consumption equipment to record and transmit relevant data to a central processing unit or a cloud server in real time. By processing and analyzing these data through data analysis software, the required power application information and power consumption data information can be obtained. Data can also be automatically collected through the energy management system (EMS) inside the building. The EMS system can monitor the operating status of the power supply equipment and the transmission status of the power supply line in real time, and obtain the power consumption data of the power consumption equipment through the interface with the smart meter and other equipment. These data will be automatically stored in the system's database for subsequent analysis.

[0034] Step S11: Differentiate the power consumption areas of the power consumption equipment based on the power application information and the equipment location information to obtain the power consumption area information of the power consumption equipment.

[0035] Specifically, the power supply area locations and power supply coverage ranges of different power supply devices are determined based on the power supply application information, and a first vector set of different power supply devices and power-consuming devices is determined based on the power supply area locations and the positions in the device location information. According to the first vector set, it is determined whether the power-consuming device is located within the power supply coverage range. If the power-consuming device is within the power supply coverage range, the power supply coverage range and the power supply devices corresponding to the power supply coverage range are summarized to obtain the power consumption area information of the power-consuming device.

[0036] For the embodiment of the present application, a geographic information system (GIS) is combined with power system analysis software. The GIS system is used to digitally process the geographic information of the building or power system, including the spatial location information of power supply equipment, power supply lines and power-consuming equipment. Then, the GIS data is imported into the power system analysis software, and combined with the power application information, the power supply area is divided and the power supply coverage is calculated. Through the algorithms and models built into the software, the optimized layout of the power supply area and the accurate calculation of the power supply coverage can be automatically completed.

[0037] In the embodiment of the present application, the first vector set represents a set of directions and distances of different power-consuming devices relative to different power supply devices. In order to accurately obtain the directions and distances between the power-consuming devices and the power supply devices in the present application, the specific expression is (power-consuming device A-power supply device B)-(35° north by west, 4 meters). In addition, the power consumption area information of the power-consuming device is used to indicate the applicable power supply devices of the power-consuming device and the power supply coverage corresponding to the applicable power supply devices.

[0038] Step S12: Generate a local power grid model corresponding to the power-consuming equipment according to the power-consuming area information and the power transmission information.

[0039] Specifically, the line length information and the environment information of the power supply line connected to the power supply equipment are determined according to the power transmission information, the group power node information of the power supply line is determined according to the line length information and the environment information, the second vector set of the power supply line and the power-consuming equipment is determined based on the node position in the group power node information and the position in the equipment location information, the power transmission association between the power-consuming equipment and the different node positions in the group power node information is constructed according to the second vector set, and the power supply line grid of the power-consuming equipment is obtained, and an initialized local model is constructed according to the power supply coverage range in the power consumption area information, and the power supply area position in the power consumption area information and the position in the equipment location information are marked in the initialized local model according to a preset ratio to obtain a marked local model, and the power supply line grid is integrated into the marked local model according to the corresponding relationship of the same power-consuming equipment, and the initial position node of each power supply line in the power supply line grid is connected with the power supply equipment corresponding to the power supply line, so as to obtain a local power grid model corresponding to the power-consuming equipment.

[0040] Specifically, determine whether the line length information meets the preset line length. If it does, determine the environmental parameters of the nodes at different positions of the power supply line based on the environmental information, and match the environmental parameters with the preset environmental coefficient standards to obtain the initial environmental coefficient of the initial position node of the power supply line and the non-initial environmental coefficient corresponding to the non-initial position node. Calculate the environmental coefficient difference between the initial environmental coefficient and each non-initial environmental coefficient, and determine the first non-initial position node that meets the preset environmental coefficient difference requirement in the environmental coefficient difference. Define the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and define the position node between the new initial position node and the final position node in the non-initial environmental coefficient as a new non-initial position node.

[0041] In the embodiment of the present application, the preset line length is a pre-set segmentable line length, that is, the line segmentation process can be performed only when the length of the power supply line meets the preset line length. The environmental parameters include the temperature and humidity data of the environment where the power supply line is located. The preset environmental coefficient standard is the standard implemented by the staff according to the different degrees of influence of different environmental parameters on the power supply line in the actual historical situation. For example, in a high temperature environment, the resistance of the power supply line will increase, and the insulation capacity of the insulating material will decrease, which may cause the line to heat up, the dielectric capacity to decrease, and even cause the line to age faster and the failure rate to increase. In addition, high temperature may also affect the working characteristics of electronic components (such as diodes, triodes, etc.), causing their performance to change. In an extremely low temperature environment, the power supply line may become inelastic, increasing the risk of fracture. Especially in severe weather such as strong winds, low temperatures may aggravate the damage to the line. Humidity causes the performance of the insulating material on the power supply line to decrease, and even causes electrochemical corrosion, thereby damaging the conductor and components. This is why it is necessary to segment the power supply lines. Because the power supply lines are located in different environments, the environmental hazards to the power supply lines are also different. The environmental coefficient in the preset environmental coefficient standard is also used to evaluate the hazard coefficient of the environment in which the current power supply lines are located.

[0042] Loop execution steps: calculate the environmental coefficient difference between the new initial environmental coefficient and each new non-initial environmental coefficient, and determine the first non-initial position node that meets the preset environmental coefficient difference requirement in the environmental coefficient difference, define the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and define the position node between the new initial position node and the final position node in the non-initial position node as a new non-initial position node. Until there is no non-initial position node that meets the preset environmental coefficient difference requirement in the environmental coefficient difference, then determine the group power node information of the power supply line based on the initial position node and the new initial position node.

[0043] The group power node information includes power transfer switches installed at the initial position node and the new initial position node and power transfer lines connected to the power transfer switches.

[0044] Specifically, the other end of the power transfer route away from the power transfer switch is connected to the initial position node of other adjacent power supply lines or the power transfer switch of the new initial position node in the coverage area of ​​the power supply device connected to the power supply line. For example: there are three power supply lines connected to the power supply device A, namely, power supply line A, power supply line B and power supply line C, wherein power supply line A is provided with an initial position node a and three new initial position nodes A1, A2, A3, power supply line B is provided with an initial position node b and two initial position nodes B1, B2, power supply line C is provided with an initial position node c and an initial position node C1, power supply line A is adjacent to power supply line B, power supply line B is adjacent to power supply line C, then the power transfer route corresponding to the initial position node a is connected to the initial position node b, the power transfer route of A1 is connected to B1, the power transfer route of A2 is connected to B2, and the power transfer route of A3 is connected to the power consumption equipment, similarly, the power transfer route of the initial position node b is connected to the initial position node c, the power transfer route of B1 is connected to C1, and the power transfer route of B2 is connected to the power consumption equipment. According to the connection mode of the power transfer routes described above, a power supply line grid of applicable power supply devices corresponding to each power-consuming device is formed.

[0045] In the embodiment of the present application, the second vector set represents the relative position and relative distance between the initial position node and the new initial position node in the group power node information of each power supply line connected to the power supply device and the position of the power consumption device. The expression form of the vector in the second vector set is (initial position node-power consumption device A) (16 degrees east by west, 6 meters), (new initial position node A-power consumption device A) (16.3 degrees east by west, 6.2 meters).

[0046] Step S13: Perform regional power consumption simulation detection on the power consumption status data according to the local power grid model to obtain the best power supply line in the power consumption area information.

[0047] For the embodiment of the present application, the best power supply line is the best route for providing electric energy to the electrical equipment in the local power grid model under ideal conditions, that is, the route with the best electricity utilization rate.

[0048] In the embodiment of the present application, when selecting the power supply line for each power-consuming device, the power application information in the building and the detailed power consumption data of the power-consuming device are fully captured and integrated. This information not only covers the historical supply capacity of the power supply equipment and the transmission status of each power supply line, but also accurately records the specific location and dynamic power consumption status of the power-consuming device. This all-round data collection lays a solid foundation for subsequent power consumption analysis and optimization. Based on the above-mentioned rich data sources, the regional segmentation of power-consuming devices is further realized. By intelligently analyzing the association between power application information and device location information, the system can accurately classify power-consuming devices into the power consumption area to which they belong. This step effectively improves the precision and pertinence of power consumption management. Subsequently, the system uses the power consumption area information and power transmission information to construct a highly restored local power grid model. This model not only reflects the physical connection structure of the power grid, but also incorporates the actual distribution of power-consuming devices and their power consumption characteristics, providing an intuitive reference for subsequent power supply optimization. Finally, according to this accurate local power grid model, it is possible to simulate and detect the power consumption status of each power consumption area under different power supply lines, and accurately identify the best power supply line through scientific calculation and comparison. This not only ensures the stability and efficiency of power supply, but also greatly reduces energy waste and achieves optimal allocation of power supply resources.

[0049] Furthermore, a regional power consumption simulation test is performed on the power consumption status data according to the local power grid model to obtain the best power supply line in the power consumption area information, which then includes: obtaining the actual power consumption information of the best power supply route, and calculating the power loss data of the group power nodes in the best power supply line based on the actual power consumption information, matching the calculated power loss value with the preset power loss standard, and determining whether the actual power consumption information meets the preset power loss standard; if the actual power consumption information does not meet the preset power loss standard, performing a power supply simulation analysis on the local power grid model to obtain a power grid layout instruction, and controlling and adjusting the line layout of the power supply lines connected to the power consuming equipment.

[0050] Specifically, multiple power supply line combinations between power supply equipment and power-consuming equipment are determined based on the local power grid model, and power consumption data changes corresponding to the group power node information of each power supply line combination in multiple power supply line combinations under the conditions of different equipment operating powers are determined. The power consumption data changes are accumulated and calculated according to the same power supply line combination to obtain the power energy consumption data corresponding to each power supply line combination, and the line scheduling length corresponding to each power supply line combination is determined according to the group power node information of each power supply line combination. The power energy consumption data and the line scheduling length are ratio-calculated to obtain the average energy consumption data of the power supply line combination, and the target power supply line combination corresponding to the minimum average energy consumption data is determined. The power transfer switch control sequence analysis is performed on the group power node information in the target power supply line combination to obtain the power grid layout instructions.

[0051] Furthermore, if the actual power consumption information does not meet the preset power loss standard, it also includes: determining the power loss data of the power supply line segment corresponding to each group power node information in the optimal power supply line based on the power loss data of the group power nodes in the optimal power supply line, calculating the ratio of the power loss data of the power supply line segment to the line segment length of the power supply line segment to obtain the power loss value of each power supply line segment, and judging whether the power loss value of each power supply line segment meets the preset power loss standard; if not, marking the line corresponding to the power supply line segment in the local power grid model to obtain the marked local power grid model.

[0052] The above embodiment introduces a smart energy management method based on IoT big data from the perspective of method flow. The following embodiment introduces a smart energy management system based on IoT big data from the perspective of virtual modules or virtual units. For details, please refer to the following embodiments.

[0053] The present application embodiment provides a smart energy management system 20 based on IoT big data, such as Figure 2 As shown, Figure 2 A schematic diagram of a smart energy management system based on IoT big data provided in an embodiment of the present application. The system 20 may specifically include: The information acquisition module 21 is used to acquire power application information and power consumption data information of power-consuming equipment, wherein the power application information is the power supply information of power supply equipment at different locations in the building during the historical period and the power transmission information of different power supply lines connected to the power supply equipment, the power-consuming equipment is the power-consuming equipment connected to the corresponding power supply line in the building during the historical period, and the power consumption data information is used to indicate the equipment location information of the power-consuming equipment and the power consumption status data of the power-consuming equipment during the historical period; A regional differentiation module 22, configured to differentiate power consumption areas of power consumption equipment based on power application information and equipment location information, and obtain power consumption area information of the power consumption equipment; A model generation module 23, used to generate a local power grid model corresponding to the power consumption equipment according to the power consumption area information and the power transmission information; The simulation detection module 24 is used to perform regional power consumption simulation detection on the power consumption status data according to the local power grid model to obtain the best power supply line in the power consumption area information.

[0054] In a possible implementation of the embodiment of the present application, the regional differentiation module 22 is specifically used to differentiate the power consumption area of ​​the power consumption equipment based on the power application information and the device location information to obtain the power consumption area information of the power consumption equipment: Determine the power supply area location and power supply coverage of different power supply devices based on the power application information; Determine a first vector set of different power supply devices and power consumption devices based on the power supply area location and the location in the device location information; Determine whether the electric device is located in the power supply coverage range according to the first vector set. If the electric device is located in the power supply coverage range, summarize the power supply coverage range and the power supply equipment corresponding to the power supply coverage range to obtain the power consumption area information of the electric device.

[0055] In another possible implementation of the embodiment of the present application, when the model generation module 23 generates a local power grid model corresponding to the power-consuming device according to the power consumption area information and the power transmission information, it is specifically used to: Determine the line length information and the environment information of the power supply line connected to the power supply device according to the power transmission information; Determine the group power node information of the power supply line according to the line length information and the environment information; Determine a second vector set of power supply lines and power-consuming devices based on the node positions in the group power node information and the positions in the device position information; According to the second vector set, electric energy transmission association is constructed between the electric equipment and different node positions in the group power node information to obtain a power supply line grid for the electric equipment; An initialization local area model is constructed according to the power supply coverage in the power consumption area information, and the power supply area location in the power consumption area information and the location in the device location information are marked in the initialization local area model according to a preset ratio to obtain a marked local area model; The power supply line grid is integrated into the marked local model according to the corresponding relationship of the same power-consuming equipment, and the initial position node of each power supply line in the power supply line grid is connected with the power supply equipment corresponding to the power supply line to obtain the local power grid model corresponding to the power-consuming equipment.

[0056] In another possible implementation of the embodiment of the present application, when the model generation module 23 determines the group power node information of the power supply line according to the line length information and the environment information, it is specifically used to: Determine whether the line length information satisfies the preset line length. If so, determine the environmental parameters of nodes at different positions of the power supply line based on the environmental information, and match the environmental parameters with the preset environmental coefficient standard to obtain the initial environmental coefficient of the initial position node of the power supply line and the non-initial environmental coefficient corresponding to the non-initial position node; Calculate the environmental coefficient difference between the initial environmental coefficient and each non-initial environmental coefficient respectively, and determine the first non-initial position node that meets the preset environmental coefficient difference requirement in the environmental coefficient difference, define the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and define the position node between the new initial position node and the final position node in the non-initial position node as a new non-initial position node; Loop execution steps: calculate the environmental coefficient difference between the new initial environmental coefficient and each new non-initial environmental coefficient, and determine the first non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement, define the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and define the environmental coefficient between the new initial position node and the final environmental coefficient in the non-initial environmental coefficient as a new non-initial position node, until there is no non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement; The group power node information of the power supply line is determined according to the initial position node and the new initial position node, and the group power node information is the power transfer switch installed at the initial position node and the new initial position node and the power transfer line connected to the power transfer switch.

[0057] In another possible implementation of the embodiment of the present application, the system 20 further includes: a power consumption information module, an energy consumption matching module and a power supply simulation module, wherein: The power consumption information module is used to obtain the actual power consumption information of the optimal power supply route and calculate the power loss data of the group power nodes in the optimal power supply route based on the actual power consumption information; An energy consumption matching module is used to match the calculated power consumption value with the preset power consumption standard to determine whether the actual power consumption information meets the preset power consumption standard; The power supply simulation module is used to perform power supply simulation analysis on the local power grid model when the actual power consumption information does not meet the preset power loss standard, obtain power grid layout instructions, and control and adjust the line layout of the power supply lines connected to the power-consuming equipment.

[0058] In another possible implementation of the embodiment of the present application, when the power supply simulation module performs power supply simulation analysis on the local power grid model and obtains the power grid layout instruction, it is specifically used to: Determine multiple power supply line combinations between power supply equipment and power consumption equipment according to the local power grid model; Determine the change in power consumption data corresponding to the group power node information of each power supply line combination in multiple power supply line combinations under the conditions of different equipment operating powers; The power consumption data changes are accumulated and calculated according to the same power supply line combination to obtain the power consumption data corresponding to each power supply line combination; Determine the line scheduling length corresponding to each power supply line combination according to the group power node information of each power supply line combination; Calculate the ratio of power consumption data and line dispatch length to obtain the average energy consumption data of the power supply line combination; The target power supply line combination corresponding to the minimum average energy consumption data is determined, and the power transfer switch control sequence analysis is performed on the group power node information in the target power supply line combination to obtain the power grid layout instruction.

[0059] Another possible implementation of the embodiment of the present application is that system 20 further includes: a loss determination module, a ratio calculation module and a line marking module, wherein: A loss determination module, used to determine the power loss data of the power supply line section corresponding to each group power node information in the best power supply line according to the power loss data of the group power nodes in the best power supply line; A ratio calculation module, used for calculating the ratio of the power loss data of the power supply line section to the line section length of the power supply line section to obtain the power loss value of each power supply line section; The line marking module is used to determine whether the power loss value of each power supply line segment meets the preset power loss standard. If not, the line corresponding to the power supply line segment in the local power grid model is marked to obtain the marked local power grid model.

[0060] Technical personnel in the relevant field can clearly understand that, for the convenience and conciseness of description, the specific working process of the smart energy management system 20 based on Internet of Things big data described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0061] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0062] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0063] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0064] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0065] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0066] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0067] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0068] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0069] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A smart energy management method based on Internet of Things big data, characterized in that: include: Acquire power application information and power consumption data information of power-consuming equipment, wherein the power application information is power supply information of power supply equipment at different locations in a building during a historical period and power transmission information of different power supply lines connected to the power supply equipment, the power-consuming equipment is the power-consuming equipment connected to the corresponding power supply line in the building during the historical period, and the power consumption data information is used to indicate the equipment location information of the power-consuming equipment and the power consumption status data of the power-consuming equipment during the historical period; Based on the power application information and the device location information, the power consumption area of ​​the power consumption device is differentiated to obtain the power consumption area information of the power consumption device; Generate a local power grid model corresponding to the power-consuming device according to the power-consuming area information and the power transmission information; The power consumption status data is subjected to regional power consumption simulation detection according to the local power grid model to obtain the best power supply line in the power consumption area information.

2. According to claim 1, a smart energy management method based on Internet of Things big data is characterized in that: The step of differentiating the power consumption area of ​​the power consumption equipment based on the power application information and the equipment location information to obtain the power consumption area information of the power consumption equipment includes: Determine the power supply area location and power supply coverage of different power supply devices based on the power application information; Determine a first vector set of different power supply devices and power-consuming devices based on the power supply area location and the location in the device location information; Determine whether the electric device is located in the power supply coverage range according to the first vector set. If the electric device is located in the power supply coverage range, summarize the power supply coverage range and the power supply equipment corresponding to the power supply coverage range to obtain the power consumption area information of the electric device.

3. According to claim 2, a smart energy management method based on Internet of Things big data is characterized in that: The generating a local power grid model corresponding to the power-consuming device according to the power-consuming area information and the power transmission information includes: Determining, according to the power transmission information, line length information and environment information of a power supply line connected to the power supply device; Determine the group power node information of the power supply line according to the line length information and the environment information; Determine a second vector set of the power supply line and the power-consuming device based on the node position in the group power node information and the position in the device position information; According to the second vector set, the power transmission association between the power-consuming device and different node positions in the group power node information is constructed to obtain a power supply line grid of the power-consuming device; Constructing an initialization local area model according to the power supply coverage in the power consumption area information, and marking the power supply area location in the power consumption area information and the location in the device location information in the initialization local area model according to a preset ratio to obtain a marked local area model; The power supply line grid is integrated into the marked local model according to the corresponding relationship of the same power-consuming equipment, and the initial position node of each power supply line in the power supply line grid is connected to the power supply equipment corresponding to the power supply line to obtain a local power grid model corresponding to the power-consuming equipment.

4. According to claim 3, a smart energy management method based on Internet of Things big data is characterized in that: The determining the group power node information of the power supply line according to the line length information and the environment information includes: Determine whether the line length information satisfies a preset line length. If so, determine the environmental parameters of nodes at different positions of the power supply line based on the environmental information, and match the environmental parameters with a preset environmental coefficient standard to obtain an initial environmental coefficient of an initial position node of the power supply line and a non-initial environmental coefficient corresponding to a non-initial position node; Calculating the environmental coefficient difference between the initial environmental coefficient and each of the non-initial environmental coefficients respectively, and determining the first non-initial position node that meets the preset environmental coefficient difference requirement in the environmental coefficient difference, defining the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and defining the position node between the new initial position node and the final position node in the non-initial environmental coefficient as a new non-initial position node; Loop execution step: calculating the environmental coefficient difference between the new initial environmental coefficient and each of the new non-initial environmental coefficients, and determining the first non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement, defining the first non-initial position node that meets the preset environmental coefficient difference requirement as a new initial position node, and defining the position node between the new initial position node and the final position node in the non-initial position node as a new non-initial position node, until there is no non-initial position node in the environmental coefficient difference that meets the preset environmental coefficient difference requirement; The group power node information of the power supply line is determined according to the initial position node and the new initial position node, and the group power node information is the power transfer switch installed at the initial position node and the new initial position node and the power transfer line connected to the power transfer switch.

5. According to claim 1, a smart energy management method based on Internet of Things big data is characterized in that: The method further comprises: performing a regional power consumption simulation test on the power consumption status data according to the local power grid model to obtain the best power supply line in the power consumption area information; and then: Acquire actual power consumption information of the optimal power supply route, and calculate power loss data of power nodes in the optimal power supply route based on the actual power consumption information; Matching the calculated power loss value with the preset power loss standard to determine whether the actual power consumption information meets the preset power loss standard; If the actual power consumption information does not meet the preset power loss standard, a power supply simulation analysis is performed on the local power grid model to obtain a power grid layout instruction, and control and adjust the line layout of the power supply line connected to the power-consuming equipment.

6. According to claim 5, a smart energy management method based on Internet of Things big data is characterized in that: The performing power supply simulation analysis on the local power grid model to obtain a power grid layout instruction includes: Determine a plurality of power supply line combinations between the power supply device and the power-consuming device according to the local power grid model; Determine the change in power consumption data corresponding to the group power node information of each power supply line combination in the plurality of power supply line combinations under the conditions of different equipment operating powers; Accumulate and calculate the power consumption data changes according to the same power supply line combination to obtain the power consumption data corresponding to each power supply line combination; Determine the line scheduling length corresponding to each power supply line combination according to the group power node information of each power supply line combination; Calculate the ratio of the power consumption data and the line scheduling length to obtain the average energy consumption data of the power supply line combination; The target power supply line combination corresponding to the minimum average energy consumption data is determined, and the power transfer switch control sequence analysis is performed on the group power node information in the target power supply line combination to obtain a power grid layout instruction.

7. The smart energy management method based on Internet of Things big data according to claim 5 is characterized in that: If the actual power consumption information does not meet the preset power loss standard, the method further includes: Determine the power loss data of the power supply line section corresponding to each power node information in the optimal power supply line according to the power loss data of the power node in the optimal power supply line; Calculating the ratio of the power loss data of the power supply line section to the line section length of the power supply line section to obtain the power loss value of each power supply line section; It is determined whether the power loss value of each power supply line segment meets the preset power loss standard. If not, the line corresponding to the power supply line segment in the local power grid model is marked to obtain a marked local power grid model.

8. A smart energy management system based on Internet of Things big data, characterized in that: include: An information acquisition module, used to acquire power application information and power consumption data information of power-consuming devices, wherein the power application information is power supply information of power supply devices at different locations in a building during a historical period and power transmission information of different power supply lines connected to the power supply devices, the power-consuming devices are power-consuming devices connected to corresponding power supply lines in the building during the historical period, and the power consumption data information is used to indicate device location information of the power-consuming devices and power consumption status data of the power-consuming devices during the historical period; A regional differentiation module, used to differentiate the power consumption area of ​​the power-consuming device based on the power application information and the device location information, and obtain the power consumption area information of the power-consuming device; A model generation module, used to generate a local power grid model corresponding to the power-consuming device according to the power consumption area information and the power transmission information; The simulation detection module is used to perform regional power consumption simulation detection on the power consumption status data according to the local power grid model to obtain the best power supply line in the power consumption area information.

9. An electronic device, characterized in that: It includes: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are configured to: execute a smart energy management method based on Internet of Things big data according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements a smart energy management method based on Internet of Things big data as described in any one of claims 1 to 7.

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